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Articles 1 - 10 of 10
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Abmscore: A Heuristic Algorithm For Forming Strategic Coalitions In Agent-Based Simulation, Andrew J. Collins, Gayane Grigoryan
Abmscore: A Heuristic Algorithm For Forming Strategic Coalitions In Agent-Based Simulation, Andrew J. Collins, Gayane Grigoryan
Engineering Management & Systems Engineering Faculty Publications
Integrating human behavior into agent-based models has been challenging due to its diversity. An example is strategic coalition formation, which occurs when an individual decides to collaborate with others because it strategically benefits them, thereby increasing the expected utility of the situation. An algorithm called ABMSCORE was developed to help model strategic coalition formation in agent-based models. The ABMSCORE algorithm employs hedonic games from cooperative game theory and has been applied to various situations, including refugee egress and smallholder farming cooperatives. This paper discusses ABMSCORE, including its mechanism, requirements, limitations, and application. To demonstrate the potential of ABMSCORE, a new …
Effects Of Individual Strategies For Resource Access On Collaboratively Maintained Irrigation Infrastructure, Jordan L. Stern, Afreen Siddiqi, Paul N. Grogan
Effects Of Individual Strategies For Resource Access On Collaboratively Maintained Irrigation Infrastructure, Jordan L. Stern, Afreen Siddiqi, Paul N. Grogan
Faculty Publications
Built infrastructure for water and energy supply, transportation, and other such services underpins human well-being and socioeconomic development. A fundamental understanding of how infrastructure design and user strategies interact can guide important design decisions as well as policy formulation for ensuring long-term infrastructure viability in conjunction with improved individual user benefits. In this work, an agent based model (ABM) is developed to study this issue for the specific case of irrigation canals. Cooperatively maintained irrigation canals serve essential roles in sustaining agriculture-based economies in many regions. Canal system design can strongly affect benefits derived by distributed users, regional agricultural output, …
Humans And The Core Partition: An Agent-Based Modeling Experiment, Andrew J. Collins, Sheida Etemadidavan
Humans And The Core Partition: An Agent-Based Modeling Experiment, Andrew J. Collins, Sheida Etemadidavan
Engineering Management & Systems Engineering Faculty Publications
Although strategic coalition formation is traditionally modeled using cooperative game theory, behavioral game theorists have repeatedly shown that outcomes predicted by game theory are different from those generated by actual human behavior. To further explore these differences, in a cooperative game theory context, we experiment to compare the outcomes resulting from human participants’ behavior to those generated by a cooperative game theory solution mechanism called the core partition. Our experiment uses an interactive simulation of a glove game, a particular type of cooperative game, to collect the participant’s decision choices and their resultant outcomes. Two different glove games are considered, …
Urban Consolidation Center Or Peer-To-Peer Platform? The Solution To Urban Last-Mile Delivery, Qiyuan Deng, Xin Fang, Yun Fong Lim
Urban Consolidation Center Or Peer-To-Peer Platform? The Solution To Urban Last-Mile Delivery, Qiyuan Deng, Xin Fang, Yun Fong Lim
Research Collection Lee Kong Chian School Of Business
The growing population in cities and booming e-commerce activities create huge demand for urban last-mile delivery, exerting intense pressure on the cities' well-being. To keep congestion and pollution under control, a consolidator can operate an urban consolidation center (UCC) to bundle shipments from multiple carriers before the last-mile delivery. Alternatively, the consolidator can operate a peer-to-peer platform for the carriers to share delivery capacity. We provide guidance for the consolidator to choose between these two business models by comparative analysis. We capture the interactions between the consolidator and carriers using a game-theoretical framework. Under each business model, the consolidator first …
Hedonic Games And Monte Carlo Simulation, Sheida Etemadidavan, Andrew J. Collins
Hedonic Games And Monte Carlo Simulation, Sheida Etemadidavan, Andrew J. Collins
Engineering Management & Systems Engineering Faculty Publications
Hedonic games have applications in economics and multi-agent systems where the grouping preferences of an individual is important. Hedonic games look at coalition formation, amongst the players, where players have a preference relation over all the coalition. Hedonic games are also known as coalition formation games, and they are a form of a cooperative game with a non-transferrable utility game. Some examples of hedonic games are stable marriage, stable roommate, and hospital/residence problem. The study of hedonic games is driven by understanding what coalition structures will be stable, i.e., given a coalition structure, no players have an incentive to deviate …
Foundations For A Game Theoretic Framework For Agile Acquisition, Scott Rosen, Kelly Horinek, Alexander Odeh, Les Servi, Andreas Tolk
Foundations For A Game Theoretic Framework For Agile Acquisition, Scott Rosen, Kelly Horinek, Alexander Odeh, Les Servi, Andreas Tolk
VMASC Publications
This article investigates the concept of developing a game theoretic framework that is based on the application of buyer and seller utility functions to support the bidding process in government acquisition. The results of a literature survey of utility function approaches, with potential to provide a suitable foundation to a game theory framework for acquisition, are presented. The utility function methods found most promising were further adapted and tested: the Best-Worst method, the Multi-Swing Method, and Functional Dependency for Network Analysis. To test the scalability of the approach, the Best-Worst method is applied to a larger problem to show the …
Direct: A Scalable Approach For Route Guidance In Selfish Orienteering Problems, Pradeep Varakantham, Hala Mostafa, Na Fu, Hoong Chuin Lau
Direct: A Scalable Approach For Route Guidance In Selfish Orienteering Problems, Pradeep Varakantham, Hala Mostafa, Na Fu, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We address the problem of crowd congestion at venues like theme parks, museums and world expos by providing route guidance to multiple selfish users (with budget constraints) moving through the venue simultaneously. To represent these settings, we introduce the Selfish Orienteering Problem (SeOP) that combines two well studied problems from literature, namely Orienteering Problem (OP) and Selfish Routing (SR). OP is a single agent routing problem where the goal is to minimize latency (or maximize reward) in traversing a subset of nodes while respecting budget constraints. SR is a game between selfish agents looking for minimum latency routes from source …
Streets: Game-Theoretic Traffic Patrolling With Exploration And Exploitation, Matthew Brown, Sandhya Saisubramanian, Pradeep Varakantham, Milind Tambe
Streets: Game-Theoretic Traffic Patrolling With Exploration And Exploitation, Matthew Brown, Sandhya Saisubramanian, Pradeep Varakantham, Milind Tambe
Research Collection School Of Computing and Information Systems
To dissuade reckless driving and mitigate accidents, cities deploy resources to patrol roads. In this paper, we present STREETS, an application developed for the city of Singapore, which models the problem of computing randomized traffic patrol strategies as a defenderattacker Stackelberg game. Previous work on Stackelberg security games has focused extensively on counterterrorism settings. STREETS moves beyond counterterrorism and represents the first use of Stackelberg games for traffic patrolling, in the process providing a novel algorithm for solving such games that addresses three major challenges in modeling and scale-up. First, there exists a high degree of unpredictability in travel times …
Sampled Fictitious Play For Multi-Action Stochastic Dynamic Programs, Archis Ghate, Shih-Fen Cheng, Stephen Baumert, Daniel Reaume, Dushyant Sharma, Robert L. Smith
Sampled Fictitious Play For Multi-Action Stochastic Dynamic Programs, Archis Ghate, Shih-Fen Cheng, Stephen Baumert, Daniel Reaume, Dushyant Sharma, Robert L. Smith
Research Collection School Of Computing and Information Systems
We introduce a class of finite-horizon dynamic optimization problems that we call multi-action stochastic dynamic programs (DPs). Their distinguishing feature is that the decision in each state is a multi-dimensional vector. These problems can in principle be solved using Bellman's backward recursion. However, complexity of this procedure grows exponentially in the dimension of the decision vectors. This is called the curse of action-space dimensionality. To overcome this computational challenge, we propose an approximation algorithm rooted in the game theoretic paradigm of Sampled Fictitious Play (SFP). SFP solves a sequence of DPs with a one-dimensional action-space, which are exponentially smaller than …
Evolving Neural Networks Applied To Predator-Evader Problem, Shivakumar Viswanathan, Ilker Ersoy, Filiz Bunyak, Cihan H. Dagli
Evolving Neural Networks Applied To Predator-Evader Problem, Shivakumar Viswanathan, Ilker Ersoy, Filiz Bunyak, Cihan H. Dagli
Computer Science Faculty Research & Creative Works
The creation of strategies to meet abstract goals is an important behavior exhibited by natural organisms. A situation requiring the development of such strategies is the predator-evader problem. To study this problem, Khepera robots are chosen as the competing agents. Using computer simulations the evolution of the adaptive behavior is studied in a predator-evader interaction. A bilaterally symmetrical multilayer perceptron neural network architecture with evolvable weights is used to model the “brains” of the agents. Evolutionary programming is employed to evolve the predator for developing adaptive strategies to meet its goals. To study the effect of learning on evolution a …