### Journal Papers (Refereed)

- P. Moriano and J. Finke, “On the formation of structure in growing networks,” Journal of Statistical Mechanics: Theory and Experiment, vol. 2013, iss. 06, p. P06010, 2013.

[Bibtex]`@article{1742-5468-2013-06-P06010, author={Pablo Moriano and Jorge Finke}, title={On the formation of structure in growing networks}, journal={Journal of Statistical Mechanics: Theory and Experiment}, volume={2013}, number={06}, pages={P06010}, url={http://stacks.iop.org/1742-5468/2013/i=06/a=P06010}, year={2013}, abstract = { Based on the formation of triad junctions, the mechanism proposed in this paper generates networks that exhibit extended rather than single power law behavior. Triad formation guarantees strong neighborhood clustering and community-level characteristics as the network size grows to infinity. The asymptotic behavior is of interest in the study of directed networks in which (i) the formation of links cannot be described according to the principle of preferential attachment, (ii) the in-degree distribution fits a power law for nodes with a high degree and an exponential form otherwise, (iii) clustering properties emerge at multiple scales and depend on both the number of links that newly added nodes establish and the probability of forming triads, and (iv) groups of nodes form modules that feature fewer links to the rest of the nodes.}, doi={10.1088/1742-5468/2013/06/P06010}, }`

- P. Moriano and J. Finke, “Power-law weighted networks from local attachments,” EPL (Europhysics Letters), vol. 99, iss. 1, p. 18002, 2012.

[Bibtex]`@article{0295-5075-99-1-18002, author={P. Moriano and J. Finke}, title={Power-law weighted networks from local attachments}, journal={EPL ({Europhysics Letters})}, volume={99}, number={1}, pages={18002}, url={http://stacks.iop.org/0295-5075/99/i=1/a=18002}, year={2012}, abstract={This letter introduces a mechanism for constructing, through a process of distributed decision-making, substrates for the study of collective dynamics on extended power-law weighted networks with both a desired scaling exponent and a fixed clustering coefficient. The analytical results show that the connectivity distribution converges to the scaling behavior often found in social and engineering systems. To illustrate the approach of the proposed framework we generate network substrates that resemble steady state properties of the empirical citation distributions of i) publications indexed by the Institute for Scientific Information from 1981 to 1997; ii) patents granted by the U.S. Patent and Trademark Office from 1975 to 1999; and iii) opinions written by the Supreme Court and the cases they cite from 1754 to 2002.}, doi={10.1209/0295-5075/99/18002}, }`

- J. Finke and K. M. Passino, “Local agent requirements for stable emergent group distributions,” IEEE Transactions on Automatic Control, vol. 56, iss. 6, pp. 1426-1431, 2011.

[Bibtex]`@article{5710392, author={Finke, J. and Passino, K.M.}, journal={{IEEE} Transactions on Automatic Control}, title={Local agent requirements for stable emergent group distributions}, year={2011}, volume={56}, number={6}, pages={1426-1431}, abstract={This note introduces a model of a generic team formation problem. We derive general conditions under which a group of scattered decision-making agents converge to a particular distribution. The desired distribution is achieved when the agents divide themselves into a fixed number of sub-groups while consenting on gains which are associated to every subgroup. The model allows us to quantify the impact of limited sensing, motion, and communication capabilities on the rate at which the distribution is achieved. Finally, we show how this theory is useful in solving a cooperative surveillance problem.}, doi={10.1109/TAC.2011.2112476}, ISSN={0018-9286}, }`

- B. J. Moore, J. Finke, and K. M. Passino, “Optimal allocation of heterogeneous resources in cooperative control scenarios,” Automatica, vol. 45, iss. 3, pp. 711-715, 2009.

[Bibtex]`@article{2008-09-007, title = "Optimal allocation of heterogeneous resources in cooperative control scenarios ", journal = "Automatica ", volume = "45", number = "3", pages = "711 - 715", year = "2009", note = "", issn = "0005-1098", doi = "10.1016/j.automatica.2008.09.007", url = "http://www.sciencedirect.com/science/article/pii/S0005109808004767", author = "Brandon J. Moore and Jorge Finke and Kevin M. Passino", keywords = "Cooperative control", keywords = "Constrained optimization", keywords = "Convex optimization", keywords = "Dynamic optimization ", abstract = "This paper introduces a mathematical framework for the study of resource allocation problems involving the deployment of heterogeneous agents to different teams. In this context, the term heterogeneous is used to describe classes of agents that differ in the basic functions they can perform (e.g., one type of agent searches for targets while another type engages those targets). The problem is addressed in terms of optimization using concepts from economic theory and the proposed algorithm was designed to ensure asymptotic stability of the optimal solution. " }`

- J. Finke, N. Quijano, and K. M. Passino, “Emergence of scale-free networks from Ideal Free Distributions,” EPL (Europhysics Letters), vol. 82, iss. 2, p. 28004, 2008.

[Bibtex]`@article{0295-5075-82-28004, author = {Jorge Finke and Nicanor Quijano and Kevin M. Passino}, title = {Emergence of scale-free networks from {Ideal Free Distributions}}, DOI= "10.1209/0295-5075/82/28004", url= "http://dx.doi.org/10.1209/0295-5075/82/28004", journal = {EPL ({Europhysics Letters})}, year = 2008, volume = 82, number = 2, pages = "28004", month = "", }`

- J. Finke and K. M. Passino, “Stable cooperative vehicle distributions for surveillance,” Journal of Dynamic Systems, Measurement, and Control, vol. 129, iss. 5, pp. 597-608, 2007.

[Bibtex]`@article{10-1115-1-2767656, Abstract = {A mathematical model for the study of the behavior of a spatially distributed group of heterogeneous vehicles is introduced. We present a way to untangle the coupling between the assignment of any vehicle's position and the assignment of all other vehicle positions by defining general sensing and moving conditions that guarantee that even when the vehicles'motion and sensing are highly constrained, they ultimately achieve a stable emergent distribution. The achieved distribution is optimal in the sense that the proportion of vehicles allocated over each area matches the relative importance of being assigned to that area. Based on these conditions, we design a cooperative control scheme for a multivehicle surveillance problem and show how the vehicles'maneuvering and sensing abilities, and the spatial characteristics of the region under surveillance, affect the desired distribution and the rate at which it is achieved.}, Annote = {10.1115/1.2767656}, Author = {Finke, Jorge and Passino, Kevin M.}, Date = {2007/01/17}, Date-Added = {2013-11-16 22:36:20 +0000}, Date-Modified = {2013-11-16 22:36:20 +0000}, Isbn = {0022-0434}, Journal = {Journal of Dynamic Systems, Measurement, and Control}, M3 = {doi: 10.1115/1.2767656}, Month = {01}, Number = {5}, Pages = {597--608}, Title = {Stable cooperative vehicle distributions for surveillance}, Ty = {JOUR}, Url = {http://dx.doi.org/10.1115/1.2767656}, Volume = {129}, Year = {2007}, Bdsk-Url-1 = {http://dx.doi.org/10.1115/1.2767656}, doi={10.1115/1.2767656}, }`

- J. Finke, K. M. Passino, and A. G. Sparks, “Stable task load balancing strategies for cooperative control of networked autonomous air vehicles,” IEEE Transactions on Control Systems Technology, vol. 14, iss. 5, pp. 789-803, 2006.

[Bibtex]`@article{1668143, author={Finke, J. and Passino, K.M. and Sparks, Andrew G.}, journal={{IEEE} Transactions on Control Systems Technology}, title={Stable task load balancing strategies for cooperative control of networked autonomous air vehicles}, year={2006}, volume={14}, number={5}, pages={789-803}, abstract={We introduce a mathematical model for the study of cooperative control problems for multiple autonomous air vehicles (AAVs) connected via a communication network. We propose a cooperative control strategy based on task-load balancing that seeks to ensure that no vehicle is underutilized and we show how to characterize task-load balancing as a stability property. Then, using Lyapunov stability analysis, we provide conditions under which task-load balancing is achieved even in the presence of communication delays. Finally, we investigate performance properties of the cooperative controller using Monte Carlo simulations. This shows the benefits of cooperation and the effects of network delays and communication topology on performance}, keywords={Lyapunov methods;Monte Carlo methods;aircraft;cooperative systems;multi-robot systems;remotely operated vehicles;stability;Lyapunov stability analysis;Monte Carlo simulations;cooperative control strategy;distributed control;multiple autonomous air vehicles;task load balancing strategies;Communication networks;Communication system control;Delay effects;Load management;Lyapunov method;Mathematical model;Mobile robots;Network topology;Remotely operated vehicles;Stability;Cooperative systems;distributed control;distributed decision making;load balancing;mobile robots}, doi={10.1109/TCST.2006.876902}, ISSN={1063-6536},}`

### Conference Proceedings (Peer-reviewed)

- K. Guerrero and J. Finke, “Dynamics of Group Cohesion in Homophilic Networks,” in Proceeding of the Conference on Decision and Control, Melbourne, Australia, 2017 (submitted).

[Bibtex]`@inproceedings{001, author={Guerrero, K. and Finke, J.}, booktitle={Proceeding of the Conference on Decision and Control}, title={Dynamics of Group Cohesion in Homophilic Networks}, year={2017 (submitted)}, abstract={Understanding cohesion and homophily in empirical networks requires analytical frameworks that capture the underlying tendency of agents to connect with similar others. This paper proposes a model of network dynamics that explains the emergence of cohesion and homophily as an aggregate outcome, at the group- and network-level, resulting from mechanisms of decision-making by heterogeneous agents. We derive conditions under which higher degrees of cohesion and homophily are reached.}, ISSN={0743-1546}, address = {Melbourne, Australia}}`

- I. Fernandez and J. Finke, “Dynamics of Degree Distributions of Social Network,” in Proceeding of the Conference on Decision and Control, Melbourne, Australia, 2017 (submitted).

[Bibtex]`@inproceedings{002, author={Fernandez, I. and Finke, J.}, booktitle={Proceeding of the Conference on Decision and Control}, title={Dynamics of Degree Distributions of Social Network}, year={2017 (submitted)}, abstract={Social network models aim to capture the complex structure of social connections. They are a framework for the design of control algorithms that take into account relationships, interactions, and communications between social actors. Based on three formation mechanisms - random attachment, triad formation, and network response - our work characterizes the dynamics of the degree distributions of social networks. In particular, we show that the complementary cumulative in- and out-degree distributions of highly clustered, reciprocal networks can be approximated by infinite dimensional time-varying linear systems. Furthermore, we derive the asymptotic behavior of both distributions and determine the invariance of the convergent sets.}, ISSN={0743-1546}, address = {Melbourne, Australia}}`

- Romero J., Salazar A., and J. Finke, “Preferential attachment with power law growth,” in Proceeding of the Conference on Decision and Control, Melbourne, Australia, 2017 (submitted).

[Bibtex]`@inproceedings{003, author={Romero, J., and Salazar, A., and Finke, J.}, booktitle={Proceeding of the Conference on Decision and Control}, title={Preferential attachment with power law growth}, year={2017 (submitted)}, abstract={The Barabasi-Albert model is commonly used to explain the formation of power laws in the degree distributions of networks. The model assumes that the principle of preferential attachment underlies network growth, that is, new nodes connects to a fixed number of nodes with a probability that is proportional to their degrees. Yet, for empirical networks the number of new edges is often not constant, but varies as more nodes become part of the network. This paper considers an extension to the original Barabasi-Albert model, in which the number of edges established by a new node follows a power law distribution with support on the total number of nodes. While most new nodes connect to a few nodes, some new nodes connect to a larger number. We first characterize the dynamics of growth of the degree of the nodes. Second, we identify sufficient conditions under which the expected value of the average degree of the network is asymptotically stable. Finally, we show how the dynamics of the model resemble the evolution of protein interaction networks, Twitter, and Facebook.}, ISSN={0743-1546}, address = {Melbourne, Australia}}`

- D. Ruiz and J. Finke, “Stability of the Jackson-Rogers model,” in Proceeding of the Conference on Decision and Control, Melbourne, Australia, 2017 (submitted).

[Bibtex]`@inproceedings{004, author={Ruiz, D. and Finke, J.}, booktitle={Proceeding of the Conference on Decision and Control}, title={Stability of the Jackson-Rogers model}, year={2017 (submitted)}, abstract={Network formation models describe the dynamics of the structure of connections using mechanisms that operate under different principles. The Jackson-Rogers model is a generic framework that captures the effects of triadic closure in growing networks. Previous results on the model focused on deriving the asymptotic behavior of the node degree distribution based on continuous-time approximations. Here, we use a discrete-time approach to characterize the resulting distribution as an invariant set, and show that this set is asymptotically stable. Furthermore, we show that the expected value of the average degree of the network is also asymptotically stable.}, ISSN={0743-1546}, address = {Melbourne, Australia}}`

- J. Campos and J. Finke, “Anomalous Node Detection in Networks with Communities of Different Size,” in Proceeding of the American Control Conference, Seattle, WA, 2017.

[Bibtex]`@inproceedings{005, author={Campos, J. and Finke, J.}, booktitle={Proceeding of the American Control Conference}, title={Anomalous Node Detection in Networks with Communities of Different Size}, year={2017}, abstract={Based on two simple mechanisms for establishing and removing links, this paper defines an event-driven model for the anomalous node detection problem. This includes a representation for (i) the tendency of regular nodes to connect with similar others (i.e., establish homophilic relationships); and (ii) the tendency of anomalous nodes to connect to random targets (i.e., establish random connections across the network). Our approach is motivated by the desire to design scalable strategies for detecting signatures of anomalous behavior, using a formal representation to take into account the evolution of network properties. In particular, we assume that regular nodes are distributed across two communities (of different size), and propose an algorithm that identifies anomalous nodes based on both geometric and spectral measures. Our focus is on defining the anomalous detection problem in a mathematical framework and to highlight key challenges when certain topological properties dominate the problem (i.e., in terms of the strength of communities and their size).}, ISSN={0743-1546}, pages = {}, address = {Seattle, WA}}`

- I. Fernandez and J. Finke, “Stability Properties of Reciprocal Networks,” in Proceeding of the American Control Conference, Boston, MA, 2016, pp. 776-781.

[Bibtex]`@inproceedings{7525008, author={Fernandez, I. and Finke, J.}, booktitle={Proceeding of the American Control Conference}, title={Stability Properties of Reciprocal Networks}, year={2016}, abstract={Models of network formation explain key features of a wide class of empirical networks based on simple mechanisms for establishing and removing links. Such mechanisms include random attachment (a generic abstraction of how a new incoming node connects to a network), triad formation (how the new node establishes transitive relationships), and network response (how the network reacts to new attachments). Our work analyses the combined effect of these three mechanisms on various local and global connectivity properties. In particular, we derive an expression for the asymptotic behavior of the local reciprocity coefficient and show that the evolution of the global reciprocity and the global clustering coefficients satisfy the dynamics of a time-varying linear system. Furthermore, we identify conditions under which the equilibrium of the system is globally asymptotically stable. Finally, we calibrate the proposed model to capture the evolution of a network composed of e-mail messages sent between members of an online community of students from the University of California, Irvine.}, ISSN={0743-1546}, pages = {776--781}, address = {Boston, MA}}`

- I. Fernandez and J. Finke, “Transitivity of Reciprocal Networks,” in Proceeding of the Conference on Decision and Control, Osaka, Japan, 2015, pp. 1625-1630.

[Bibtex]`@inproceedings{07402443, author={Fernandez, I. and Finke, J.}, booktitle={Proceeding of the Conference on Decision and Control}, title={Transitivity of Reciprocal Networks}, year={2015}, abstract={Network models are a useful tool to describe and predict dynamic relationships in large collections of data. Characterizing these relationships allows us to explain the emergence of underlying structures and estimate the expected degrees of uncertainty in connectivity patterns. This paper introduces an event-driven model that captures the effects of three simple network formation mechanisms: random attachment (a generic abstraction of how an incoming node connects to a network), triad formation (its impact on new neighbors), and network response (i.e., the way the overall network reacts to new attachments). Our work focuses on the impact of network response on the in- and out-degree distributions and the local clustering coefficients. In particular, we prove that under the proposed mechanisms any initial network reaches a stationary degree distribution with stationary clustering properties. Simulation results suggest that the response mechanism amplifies the scaling behavior of the degree distribution, originally induced by random attachment and triad formation.}, ISSN={0743-1546}, pages = {1625--1630}, address = {Osaka, Japan}}`

- P. Moriano and J. Finke, “Model-based Fraud Detection in Growing Networks,” in Proceeding of the Conference on Decision and Control, Los Angeles, CA, 2014, pp. 6068-6073.

[Bibtex]`@inproceedings{7040339, author={Moriano, P. and Finke, J.}, booktitle={Proceeding of the Conference on Decision and Control}, title={Model-based Fraud Detection in Growing Networks}, year={2014}, pages={6068 - 6073}, abstract={People share opinions, exchange information, and trade services on large, interconnected platforms. Because of the size of these platforms, they are common targets for fraudsters who try to deceive randomly selected users. To monitor such behavior, the proposed algorithm evaluates anomalies in the network structure that results from local interactions between users. In particular, the algorithm evaluates the degree of membership to well-defined communities of users and the formation of close-knit groups in their neighborhoods. We identify a set of suspects using a first order approximation of the evolution of the eigenpairs associated to the network; and within the set of suspects, we locate fraudsters based on deviations from the expected local clustering coefficients. Simulations illustrate how incorporating structural properties (their asymptotic behavior) into the design of the algorithm allows us to differentiate between the aggregate dynamics of fraudsters and regular users.}, ISSN={0743-1546}, address = {Los Angeles, CA}}`

- I. Fernandez and J. Finke, “On the stability of resource undermatching in human group-choice,” in Proceedings of the American Control Conference, Portland, OR, 2014, pp. 2059-2064.

[Bibtex]`@inproceedings{6858908, author={Fernandez, I. and Finke, J.}, booktitle={Proceedings of the American Control Conference}, title={On the stability of resource undermatching in human group-choice}, year={2014}, pages={2059-2064}, abstract={The analysis of patterns of social interaction plays an important role in providing services on online platforms (e.g., in designing algorithms for the allocation of information resources). The proposed model takes into account human factors underlying the concept of the Ideal Free Distribution (IFD), which captures empirical patterns of the aggregate group-level behavior of individuals competing for resources. The model explains the phenomenon of resource undermatching as a natural IFD-based outcome resulting from boundedly rational decision-making (i.e., individuals perceive only some of the available resources). We show that undermatching can be described as a globally balanced state in which the perceived cost of the best forgone alternatives is approximately the same for all individuals. Furthermore, we identify conditions that guarantee stability. From this analysis, we infer that the matching of the aggregate of individual choices to resources is independent of their initial distribution. Finally, we quantify the effect of resource scarcity on the degree of matching.}, keywords={behavioral sciences;decision making;human factors;IFD;dynamic model;empirical dispersal patterns;human decision-making;human factors;ideal free distributions;large-scale distributed applications;population-dependent equilibrium point;uncertainty reduction;Asymptotic stability;Decision making;Human factors;Nickel;Sensitivity;Stability criteria}, ISSN={0743-1619}, address = {Portland, OR}}`

- P. Moriano and J. Finke, “Characterizing the relationship between degree distributions and community structures,” in Proceedings of the American Control Conference, Portland, OR, 2014, pp. 2383-2388.

[Bibtex]`@inproceedings{6858882, author={Moriano, P. and Finke, J.}, booktitle={Proceedings of the American Control Conference}, title={Characterizing the relationship between degree distributions and community structures}, year={2014}, pages={2383-2388}, abstract={Extended power laws and inhomogeneous connections are structural patterns often found in empirical networks. Mechanisms based on the formation of triads are able to explain the power law behavior of the degree distribution of such networks. The proposed model introduces a two-step mechanism of attachment and triad formation that illustrates how preferential linkage plays an important role in shaping the inhomogeneity of connections and the division of the network into groups of nodes (i.e., the growth of community structures). In particular, we identify conditions under which the scaling exponent of the power law correlates to a widely-used modularity measure of non-overlapping communities. Our analytical results characterize the asymptotic behavior of both the scaling exponent and the modularity, as a function of the strength with which nodes with similar characteristics tend to link to each other.}, keywords={pattern clustering;probability;extended power law behavior;growing network structure;in-degree distribution;link formation;preferential attachment principle;strong neighborhood clustering;triad junction formation probability;Analytical models;Indexes;Junctions;Patents;Probability distribution;Random processes;Random variables}, ISSN={0743-1619}, address = {Portland, OR}}`

- D. Ruiz and J. Finke, “Invalidation of dynamic network models,” in Proceedings of the American Control Conference, Washington, DC, 2013, pp. 138-143.

[Bibtex]`@inproceedings{6579827, author={Ruiz, D. and Finke, J.}, booktitle={Proceedings of the American Control Conference}, title={Invalidation of dynamic network models}, year={2013}, pages={138-143}, abstract={Models of discrete event systems combine ideas from control theory and computer science to represent the evolution of distributed processes. We formalize a notion of the invalidation of models presumed to describe dynamics on networks, and introduce an algorithm to evaluate a class of event-driven processes that evolve close to an invariant and stable state. The algorithm returns the value true, if according to the proposed notion of invalidation, the evolution of empirical observations is inconsistent with the stability properties of the model. To illustrate the approach, we represent a generic decision-making process in which the marginal utility of allocating agents to particular nodes rests on the well-known concept in economy theory of the law of diminishing returns.}, keywords={discrete event systems;stability;discrete event system;distributed process;dynamic network model;event-driven process;generic decision-making process;marginal utility;stability property;Biological system modeling;Discrete-event systems;Heuristic algorithms;Resource management;Stability analysis;Trajectory;Vectors}, ISSN={0743-1619}, address = {Washington, DC}}`

- I. Fernandez, J. Finke, and D. Ruiz, “Ideal Free Distributions in human decision-making,” in Proceedings of the American Control Conference, Washington, DC, 2013, pp. 917-922.

[Bibtex]`@inproceedings{6579953, author={Fernandez, I. and Finke, J. and Ruiz, D.}, booktitle={Proceedings of the American Control Conference}, title={Ideal Free Distributions in human decision-making}, year={2013}, pages={917-922}, abstract={Integrating human factors into the design of large-scale distributed applications requires capturing broad patterns of decision-making over time. The proposed theoretical framework introduces a dynamic model that resembles empirical dispersal patterns between the quality of an option and the number of individuals choosing that option. We use the notion of the Ideal Free Distribution (IFD) to estimate the resulting population-dependent equilibrium point and reduce uncertainty about how groups of individuals choose between available options. Our contribution is twofold. First, we identify conditions that lead to the IFD under constrained choice. Second, we illustrate how biases in decision-making can lead to systemic deviations from the IFD.}, keywords={behavioural sciences;decision making;human factors;IFD;dynamic model;empirical dispersal patterns;human decision-making;human factors;ideal free distributions;large-scale distributed applications;population-dependent equilibrium point;uncertainty reduction;Asymptotic stability;Decision making;Human factors;Nickel;Sensitivity;Stability criteria}, ISSN={0743-1619}, address = {Washington, DC}}`

- P. Moriano and J. Finke, “Structure of growing networks with no preferential attachment,” in Proceedings of the American Control Conference, Washington, DC, 2013, pp. 1088-1093.

[Bibtex]`@inproceedings{6579981, author={Moriano, P. and Finke, J.}, booktitle={Proceedings of the American Control Conference}, title={Structure of growing networks with no preferential attachment}, year={2013}, pages={1088-1093}, abstract={Based on the formation of triad junctions, the proposed mechanism generates growing networks that exhibit extended power law behavior and strong neighborhood clustering. The asymptotic behavior of both properties is of interest in the study of networks in which (i) the formation of links cannot be described according to the principle of preferential attachment; (ii) the in-degree distribution fits a power law for nodes with a high degree and an exponential form otherwise; and (iii) the degree of clustering depends on both the number of links that newly added nodes establish and the probability of forming triads.}, keywords={pattern clustering;probability;extended power law behavior;growing network structure;in-degree distribution;link formation;preferential attachment principle;strong neighborhood clustering;triad junction formation probability;Analytical models;Indexes;Junctions;Patents;Probability distribution;Random processes;Random variables}, ISSN={0743-1619}, address = {Washington, DC}}`

- J. M. Nogales and J. Finke, “Optimal distribution of heterogeneous agents under delays,” in Proceedings of the American Control Conference, Washington, DC, 2013, pp. 3212-3217.

[Bibtex]`@inproceedings{6580326, author={Nogales, J.M. and Finke, J.}, booktitle={Proceedings of the American Control Conference}, title={Optimal distribution of heterogeneous agents under delays}, year={2013}, pages={3212-3217}, abstract={An analytical framework for the study of a generic distribution problem is introduced in which a group of agents with different capabilities intend to maximize total utility by dividing themselves into various subgroups without any form of global information-sharing or centralized decision-making. The marginal utility of belonging to a particular subgroup rests on the well-known concept in economic theory of the law of diminishing returns. For a class of discrete event systems, we identify a set of conditions that define local information and cooperation requirements, and prove that if the proposed conditions are satisfied a stable agent distribution representing a Pareto optimum is achieved even under random but bounded decision and transition delays.}, keywords={Pareto analysis;decision making;multi-agent systems;Pareto optimum;centralized decision making;economic theory;generic distribution problem;global information sharing;optimal heterogeneous agent distribution;stable agent distribution;transition delays;Decision making;Delays;Discrete-event systems;Economics;Indexes;Sensors;Vectors}, ISSN={0743-1619}, address = {Washington, DC}}`

- K. Guerrero and J. Finke, “On the formation of community structures from homophilic relationships,” in Proceedings of the American Control Conference, Montreal, QC, 2012, pp. 5318-5323.

[Bibtex]`@inproceedings{6315325, author={Guerrero, K. and Finke, J.}, booktitle={Proceedings of the American Control Conference}, title={On the formation of community structures from homophilic relationships}, year={2012}, pages={5318-5323}, abstract={Many real-world networks consist of numerous interconnected groups which, as communities, display distinctive collective behavior. The division of a network into communities-groups of nodes with a high density of ties within but a low density of ties between groups- underlies the structure of social and technological networks. In human communities, for instance, individuals may group together according to special interest, occupation, intent, or belief, with tendency to establish stronger ties with individuals who are similar to themselves. Here, we introduce a formal framework for the formation of community structures from homophilic relationships between individuals. Stochastic modeling of local relationships allows us to identify a wide class of agent interactions which lead to the formation of communities and quantify the extent to which group size affects the resulting structure.}, keywords={group theory;network theory (graphs);stochastic processes;agent interactions;community structure formation;homophilic relationships;human communities;interconnected groups;real-world networks;social network structure;technological network structure;Communities;Decision making;Indexes;Joining processes;Markov processes;Transient analysis}, ISSN={0743-1619}, address = {Montreal, QC}}`

- J. M. Nogales and J. Finke, “Local requirements for optimal distribution of heterogeneous agents,” in Proceeding of the Conference on Decision and Control and the European Control Conference, Orlando, FL, 2011, pp. 3596-3601.

[Bibtex]`@inproceedings{6161376, author={Nogales, J.M. and Finke, J.}, booktitle={Proceeding of the Conference on Decision and Control and the European Control Conference}, title={Local requirements for optimal distribution of heterogeneous agents}, year={2011}, pages={3596-3601}, abstract={This paper introduces an analytical framework for the study of a generic distribution problem where a group of heterogeneous agents intend to divide themselves into various subgroups without any form of global information-sharing or centralized decision-making. Subgroups are associated to mathematical functions that capture the marginal utilities of performing tasks, each satisfying the law of diminishing returns. We prove that under generic local requirements a stable agent distribution representing a Nash equilibrium can be achieved, and show via Monte Carlo simulations how the proposed set of rules performs under varying constraints on information flow and degrees of cooperation.}, keywords={Monte Carlo methods;functions;game theory;system theory;Monte Carlo simulations;Nash equilibrium;cooperation degree;diminishing returns law;generic distribution problem;generic local requirements;information flow;marginal utilities;mathematical functions;optimal heterogeneous agent distribution;stable agent distribution;subgroups;Companies;Indexes;Measurement;Monte Carlo methods;Nash equilibrium;Vectors}, ISSN={0743-1546}, address = {Orlando, FL}}`

- P. Moriano and J. Finke, “Heavy-tailed weighted networks from local attachment strategies,” in Proceeding of the Conference on Decision and Control and the European Control Conference, Orlando, FL, 2011, pp. 5211-5216.

[Bibtex]`@inproceedings{6161494, author={Moriano, P. and Finke, J.}, booktitle={Proceeding of the Conference on Decision and Control and the European Control Conference}, title={Heavy-tailed weighted networks from local attachment strategies}, year={2011}, pages={5211-5216}, abstract={Large networks arise by the gradual addition of nodes attaching to an existing and evolving network component. There are a wide class of attachment strategies which lead to distinct structural features in growing networks. This paper introduces a mechanism for constructing, through a process of distributed decision-making, substrates for the study of collective dynamics on power-law weighted networks with both a desired scaling exponent and a desired clustering coefficient. The analytical results show that the connectivity distribution converges to the scaling behavior often found in social and engineering systems. To illustrate the approach of the proposed framework we generate network substrates that resemble the empirical citation distributions of (i) patents granted by the U.S. Patent and Trademark Office from 1975 to 1999; and (ii) opinions written by the Supreme Court and the cases they cite from 1754 to 2002.}, keywords={citation analysis;decision making;information networks;network theory (graphs);clustering coefficient;connectivity distribution;distributed decision making;empirical citation distribution;engineering system;heavy-tailed weighted network component;local attachment strategy;power law weighted network substrate;scaling behavior;social system;Asymptotic stability;Complex networks;Conferences;Mathematical model;Patents;Probability distribution;Trajectory}, ISSN={0743-1546}, address={Orlando, FL}}`

- J. Finke, B. J. Moore, and K. M. Passino, “Stable emergent agent distributions under sensing and travel delays,” in Proceeding of the Conference on Decision and Control, Cancun, Mexico, 2008, pp. 1809-1814.

[Bibtex]`@inproceedings{4738797, author={Finke, J. and Moore, B.J. and Passino, K.M.}, booktitle={Proceeding of the Conference on Decision and Control}, title={Stable emergent agent distributions under sensing and travel delays}, year={2008}, pages={1809-1814}, abstract={In order for a team of cooperating agents to achieve a group goal (such as searching for targets, monitoring an environment, etc.) those agents must be able to share information and achieve some level of coordination. Since realistic methods of communication between agents have limited range and speed, the agentsÃ‚Â¿ decision-making strategies must operate with incomplete and outdated information. Moreover, in many situations the agents must travel to particular locations in order to perform various tasks, and so there will also be a delay between any particular decision and its effect. In this paper we develop an asynchronous framework that models the behavior of a group of agents that is spatially distributed across a predefined area of interest. We derive general conditions under which the group is guaranteed to converge to a specific distribution within the environment without any form of central control and despite unknown but bounded delays in sensing and travel. The achieved distribution is optimal in the sense that the proportion of agents allocated over each area matches the relative importance of that area. Finally, based on the derived conditions, we design a cooperative control scheme for a multi-agent surveillance problem. Via Monte Carlo simulations we show how sensing and travel delays and the degree of cooperation between agents affect the rate at which they achieve the desired coverage of the region under surveillance.}, keywords={Monte Carlo methods;control engineering computing;cooperative systems;decision making;delay systems;multi-robot systems;Monte Carlo simulations;agent distributions;asynchronous framework;cooperating agents;cooperative control scheme;decision-making strategies;travel delays;Centralized control;Communication system control;Computerized monitoring;Control systems;Cooperative systems;Decision making;Delay effects;Distributed computing;Distributed decision making;Surveillance}, ISSN={0191-2216}, address={Cancun, Mexico}}`

- J. Finke, N. Quijano, and K. M. Passino, “Ideal Free Distributions in growing networks,” in Proceeding of the American Control Conference, Seattle, WA, 2008, pp. 159-164.

[Bibtex]`@inproceedings{4586484, author={Finke, J. and Quijano, N. and Passino, K.M.}, booktitle={Proceeding of the American Control Conference}, title={{Ideal Free Distributions} in growing networks}, year={2008}, pages={159-164}, abstract={This paper presents a class of network optimization processes that account for the emergence of scale-free network structures. We introduce a mathematical framework that captures the connectivity and growth dynamics of a network with an arbitrary initial topology. We show how selection via differential node fitness affects the proportion of connections a node makes to other nodes, and how a heavy-tailed connectivity behavior manifests itself from consecutive achievements of ideal free distributions (IFDs). Finally, we present simulation results that show how this class of networks may emerge even when consecutive IFDs are not perfectly reached.}, keywords={complex networks;graph theory;network theory (graphs);optimisation;statistical distributions;graph theory;heavy-tailed connectivity behavior;ideal free distribution;mathematical framework;network growth dynamics;network optimization;scale-free network structures;topology;Acceleration;Collaborative work;Computational modeling;Computer networks;Equations;Interconnected systems;Network topology;Networked control systems;Proteins;Web sites}, ISSN={0743-1619}, address={Seattle, WA}}`

- J. Finke and K. M. Passino, “Stable emergent heterogeneous agent distributions in noisy environments,” in American Control Conference, Minneapolis, MN, 2006, pp. 6-14.

[Bibtex]`@inproceedings{1656534, author={Finke, J. and Passino, K.M.}, booktitle={American Control Conference}, title={Stable emergent heterogeneous agent distributions in noisy environments}, year={2006}, pages={6--14}, abstract={A mathematical model is introduced for the study of the behavior of a spatially distributed group of heterogenous agents which possess noisy assessments of the state of their immediate surroundings. We define general sensing and motion conditions on the agents that guarantee the emergence of a type of "ideal free distribution" (IFD) across the environment, and focus on how individual and environmental characteristics affect this distribution. In particular, we show the impact of the agents' maneuvering and sensing abilities for different classes of environments, and how spatial constraints of the environment affect the rate at which the distribution is achieved. Finally, we apply this model to a cooperative vehicle control problem and present simulation results that show the benefits of an IFD-based distributed decision-making strategy}, keywords={Lyapunov methods;multi-agent systems;stability;vehicles;agent maneuvering;agent sensing;cooperative vehicle control;decision-making strategy;ideal free distribution;mathematical model;noisy environments;spatial constraints;spatially distributed group;stable emergent heterogeneous agent distributions;Animals;Biological system modeling;Collaborative work;Costs;Distributed decision making;Environmental factors;Mathematical model;Topology;Vehicle dynamics;Working environment noise}, address={Minneapolis, MN}}`

- J. Finke and K. M. Passino, “Stable cooperative multiagent spatial distributions,” in Proceeding of the Conference on Decision and Control and the European Control Conference, Sevilla, Spain, 2005, pp. 3566-3571.

[Bibtex]`@inproceedings{1582715, author={Finke, J. and Passino, K.M.}, booktitle={Proceeding of the Conference on Decision and Control and the European Control Conference}, title={Stable cooperative multiagent spatial distributions}, year={2005}, pages={3566-3571}, abstract={This paper introduces a mathematical model of the behavior of a group of agents and their interactions in a shared environment. We represent environmental spatial constraints that allow us to model range-limited sensing, motion, and communication capabilities of the agents. We derive general sensing, coordination, and motion conditions on the agents that guarantee that an "ideal free distribution" (IFD) of the group of agents will emerge across the environment. We show the impact of group size on the distribution of agents, and consider the emergent distribution for different classes of environments. Finally, we show how this theory is useful in solving a multivehicle cooperative surveillance problem.}, keywords={Animals;Collaborative work;Costs;Environmental factors;Interference;Mathematical model;Nash equilibrium;Sparks;Surveillance;Topology}, address={Sevilla, Spain}}`

- J. Finke, K. M. Passino, and A. Sparks, “Cooperative control via task load balancing for networked uninhabited autonomous vehicles,” in Proceedings of the Conference on Decision and Control, Maui, HI, 2003, pp. 31-36.

[Bibtex]`@inproceedings{1272531, author={Finke, J. and Passino, K.M. and Sparks, A.}, booktitle={Proceedings of the Conference on Decision and Control}, title={Cooperative control via task load balancing for networked uninhabited autonomous vehicles}, year={2003}, volume={1}, pages={31-36}, abstract={In this paper we first define a mathematical model of the "plant" for the cooperative control problem for multiple uninhabited autonomous vehicles (UAVs). This includes a representation for the vehicles, environment, and communication network. Next, we define an approach to cooperative control that uses local UAV task planning and multi-UAV coordination via task load balancing over the communication network. Our approach is motivated by our desire to cope with significant imperfections in the communication network and uncertainty in the environment, and yet provide a scalable strategy which can be implemented in real time across a network of UAVs, each of which only has relatively low processing power. Our focus in this paper is on defining the cooperative controller problem in a mathematical framework that is familiar to a control engineer, studying properties of a load balancing strategy for cooperation, and then via simulations to identify key challenges when network influences dominate the problem.}, keywords={mobile robots;multi-robot systems;remotely operated vehicles;resource allocation;communication network;cooperative control;load balancing strategy;mobile robots;multiple uninhabited autonomous vehicles;multirobot systems;networked uninhabited autonomous vehicles;simulation;task planning;uncertainty environments;Communication networks;Communication system control;Delay effects;Load management;Mathematical model;Mobile robots;Remotely operated vehicles;Sparks;Uncertainty;Unmanned aerial vehicles}, ISSN={0191-2216}, address={Maui, HI}}`

### Book Chapters

- J. Finke, K. M. Passino, S. Ganapathy, and A. Sparks, “Modeling and analysis of cooperative control systems for uninhabited autonomous vehicles,” in Cooperative Control, V. Kumar, N. Leonard, and A. Morse, Eds., Springer Berlin Heidelberg, 2005, vol. 309, pp. 79-102.

[Bibtex]`@incollection{978-3-540-31595-7_5, year={2005}, isbn={978-3-540-22861-5}, booktitle={Cooperative Control}, volume={309}, series={Lecture Notes in Control and Information Science}, editor={Kumar, Vijay and Leonard, Naomi and Morse, A.Stephen}, doi={10.1007/978-3-540-31595-7_5}, title={Modeling and analysis of cooperative control systems for uninhabited autonomous vehicles}, url={http://dx.doi.org/10.1007/978-3-540-31595-7_5}, publisher={Springer Berlin Heidelberg}, author={Finke, Jorge and Passino, Kevin M. and Ganapathy, Sriram and Sparks, Andrew}, pages={79-102},}`

- J. Finke and K. Passino, “The ecological Ideal Free Distribution and distributed networked control systems,” in Unifying Themes in Complex Systems, A. Minai, D. Braha, and Y. Bar-Yam, Eds., Springer Berlin Heidelberg, 2011, pp. 128-135.

[Bibtex]`@incollection{978-3-642-17635-7_16, year={2011}, isbn={978-3-642-17634-0}, booktitle={Unifying Themes in Complex Systems}, editor={Minai, AliA. and Braha, Dan and Bar-Yam, Yaneer}, doi={10.1007/978-3-642-17635-7_16}, title={The ecological {Ideal Free Distribution} and distributed networked control systems}, url={http://dx.doi.org/10.1007/978-3-642-17635-7_16}, publisher={Springer Berlin Heidelberg}, author={Finke, Jorge and Passino, KevinM.}, pages={128-135}, language={English},}`

### Other Publications

- J. V. Barr, E. M. Pinilla, and J. Finke, “A legal perspective on the use of models in the fight against corruption,” South Carolina Journal of International Law and Business, vol. 8, iss. 2, pp. 267-296, 2012.

[Bibtex]`@article{822012, author={J. V. Barr and E. M. Pinilla and J. Finke}, title={A legal perspective on the use of models in the fight against corruption}, journal={South Carolina Journal of International Law and Business}, volume={8}, number={2}, pages={267-296}, url={http://scholarcommons.sc.edu/scjilb/vol8/iss2/5}, year={2012}, }`

- P. Moriano, J. Finke, and Y. -Y. Ahn, “Community-based anomalous event detection in temporal networks,” in Conference on Complex Systems, Cancun, Mexico, 2017.

[Bibtex]`@inproceedings{822013, author={P. Moriano and J. Finke and Y.-Y Ahn}, title={Community-based anomalous event detection in temporal networks}, booktitle ={Conference on Complex Systems}, month={September}, address={Cancun, Mexico}, year={2017}, abstract={Communication networks exhibit community structure based on demographic, geographic, and topical homophily. Members of each community tend to have common interests and to share most contents primarily within their community, exhibiting behavioral characteristics of complex contagion. By contrast, previous studies have shown that viral contents tend to behave like simple contagion, easily crossing community boundaries. We hypothesize that contents about an important event tend to be viral because they are relevant to a large fraction of people in the network, and that the increase in viral contents due to the event will trigger more communication across existing communities. We conrm our hypothesis and demonstrate that it can be used to detect anomalous events from temporal communication network structure, namely by monitoring and comparing the communication volume within and across communities. We use two examples|the collapse of Enron and the Boston Marathon bombing|to show that the communication volume across communities indeed increases when the information about the events was spreading across the communication network.} }`