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Articles 1 - 20 of 20
Full-Text Articles in Entire DC Network
Sliding Markov Decision Processes For Dynamic Task Planning On Uncrewed Aerial Vehicles, Trent Wiens
Sliding Markov Decision Processes For Dynamic Task Planning On Uncrewed Aerial Vehicles, Trent Wiens
Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research
Mission and flight planning problems for uncrewed aircraft systems (UASs) are typically large and complex in space and computational requirements. With enough time and computing resources, some of these problems may be solvable offline and then executed during flight. In dynamic or uncertain environments, however, the mission may require online adaptation and replanning. In this work, we will discuss methods of creating MDPs for online applications, and a method of using a sliding resolution and receding horizon approach to build and solve Markov Decision Processes (MDPs) in practical planing applications for UASs. In this strategy, called a Sliding Markov Decision …
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 …
Real-Time Hierarchical Map Segmentation For Coordinating Multi-Robot Exploration, Tianze Luo, Zichen Chen, Budhitama Subagdja, Ah-Hwee Tan
Real-Time Hierarchical Map Segmentation For Coordinating Multi-Robot Exploration, Tianze Luo, Zichen Chen, Budhitama Subagdja, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Coordinating a team of autonomous agents to explore an environment can be done by partitioning the map of the environment into segments and allocating the segments as targets for the individual agents to visit. However, given an unknown environment, map segmentation must be conducted in a continuous and incremental manner. In this paper, we propose a novel real-time hierarchical map segmentation method for supporting multi-agent exploration of indoor environments, wherein clusters of regions of segments are formed hierarchically from randomly sampled points in the environment. Each cluster is then assigned with a cost-utility value based on the minimum cost possible …
Reinforcement Learning For Zone Based Multiagent Pathfinding Under Uncertainty, Jiajing Ling, Tarun Gupta, Akshat Kumar
Reinforcement Learning For Zone Based Multiagent Pathfinding Under Uncertainty, Jiajing Ling, Tarun Gupta, Akshat Kumar
Research Collection School Of Computing and Information Systems
We address the problem of multiple agents finding their paths from respective sources to destination nodes in a graph (also called MAPF). Most existing approaches assume that all agents move at fixed speed, and that a single node accommodates only a single agent. Motivated by the emerging applications of autonomous vehicles such as drone traffic management, we present zone-based path finding (or ZBPF) where agents move among zones, and agents' movements require uncertain travel time. Furthermore, each zone can accommodate multiple agents (as per its capacity). We also develop a simulator for ZBPF which provides a clean interface from the …
Hierarchical Multiagent Reinforcement Learning For Maritime Traffic Management, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau
Hierarchical Multiagent Reinforcement Learning For Maritime Traffic Management, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Increasing global maritime traffic coupled with rapid digitization and automation in shipping mandate developing next generation maritime traffic management systems to mitigate congestion, increase safety of navigation, and avoid collisions in busy and geographically constrained ports (such as Singapore's). To achieve these objectives, we model the maritime traffic as a large multiagent system with individual vessels as agents, and VTS (Vessel Traffic Service) authority as a regulatory agent. We develop a hierarchical reinforcement learning approach where vessels first select a high level action based on the underlying traffic flow, and then select the low level action that determines their future …
Establishing Rules For Self-Organizing Systems-Of-Systems, David M. Curry, Cihan H. Dagli
Establishing Rules For Self-Organizing Systems-Of-Systems, David M. Curry, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
Self-organizing systems-of-systems offer the possibility of autonomously adapting to new circumstances and tasking. This could significantly benefit large endeavors such as smart cities and national defense by increasing the probability that new situations are expediently handled. Complex self-organizing behaviors can be produced by a large set of individual agents all following the same simple set of rules. While biological rule sets have application in achieving human goals, other rules sets may be necessary as these goals are not necessarily mirrored in nature. To this end, a set of system, rather than biologically, inspired rules is introduced and an agent-based model …
A Multi-Agent System For Coordinating Vessel Traffic, Teck-Hou Teng, Hoong Chuin Lau, Akshat Kumar
A Multi-Agent System For Coordinating Vessel Traffic, Teck-Hou Teng, Hoong Chuin Lau, Akshat Kumar
Research Collection School Of Computing and Information Systems
Environmental, regulatory and resource constraints affects the safety and efficiency of vessels navigating in and out of the ports. Movement of vessels under such constraints must be coordinated for improving safety and efficiency. Thus, we frame the vessel coordination problem as a multi-agent path-finding (MAPF) problem. We solve this MAPF problem using a Coordinated Path-Finding (CPF) algorithm. Based on the local search paradigm, the CPF algorithm improves on the aggregated path quality of the vessels iteratively. Outputs of the CPF algorithm are the coordinated trajectories. The Vessel Coordination Module (VCM) described here is the module encapsulating our MAPF-based approach for …
Evolutionary Algorithm Based Approach For Modeling Autonomously Trading Agents, Anil Yaman, Stephen Lucci, Izidor Gertner
Evolutionary Algorithm Based Approach For Modeling Autonomously Trading Agents, Anil Yaman, Stephen Lucci, Izidor Gertner
Publications and Research
The autonomously trading agents described in this paper produce a decision to act such as: buy, sell or hold, based on the input data. In this work, we have simulated autonomously trading agents using the Echo State Network (ESNs) model. We generate a collection of trading agents that use different trading strategies using Evolutionary Programming (EP). The agents are tested on EUR/ USD real market data. The main goal of this study is to test the overall performance of this collection of agents when they are active simultaneously. Simulation results show that using different agents concurrently outperform a single agent …
Shape Control Of Cyclic Networks In Multirobot Formations, Tolga Eren
Shape Control Of Cyclic Networks In Multirobot Formations, Tolga Eren
Turkish Journal of Electrical Engineering and Computer Sciences
The first part of this paper examines cycles at the network level of sensing and control architectures that are needed to maintain the shape of a multiagent formation in 2-dimensional space, while the formation moves as a cohesive whole. The key tools used in the paper are rigidity theory and graph theory. The second part of the paper focuses on the planner level and controller level of the architecture by designing the fuzzy planner and fuzzy controller of individual agents. This permits the decomposition of the complex coordination problem into a series of smaller ones. The fuzzy planner and the …
Active Malware Analysis Using Stochastic Games, Simon Williamson, Pradeep Reddy Varakantham, Debin Gao, Chen Hui Ong
Active Malware Analysis Using Stochastic Games, Simon Williamson, Pradeep Reddy Varakantham, Debin Gao, Chen Hui Ong
Research Collection School Of Computing and Information Systems
Cyber security is increasingly important for defending computer systems from loss of privacy or unauthorised use. One important aspect is threat analysis - how does an attacker infiltrate a system and what do they want once they are inside. This paper considers the problem of Active Malware Analysis, where we learn about the human or software intruder by actively interacting with it with the goal of learning about its behaviours and intentions, whilst at the same time that intruder may be trying to avoid detection or showing those behaviours and intentions. This game-theoretic active learning is then used to obtain …
A Trust-Based Multiagent System, Richard S. Seymour, Gilbert L. Peterson
A Trust-Based Multiagent System, Richard S. Seymour, Gilbert L. Peterson
Faculty Publications
Cooperative agent systems often do not account for sneaky agents who are willing to cooperate when the stakes are low and take selfish, greedy actions when the rewards rise. Trust modeling often focuses on identifying the appropriate trust level for the other agents in the environment and then using these levels to determine how to interact with each agent. Adding trust to an interactive partially observable Markov decision process (I-POMDP) allows trust levels to be continuously monitored and corrected enabling agents to make better decisions. The addition of trust modeling increases the decision process calculations, and solves more complex trust …
Intentional Learning Agent Architecture, Budhitama Subagdja, Liz Sonenberg, Iyad Rahwan
Intentional Learning Agent Architecture, Budhitama Subagdja, Liz Sonenberg, Iyad Rahwan
Research Collection School Of Computing and Information Systems
Dealing with changing situations is a major issue in building agent systems. When the time is limited, knowledge is unreliable, and resources are scarce, the issue becomes more challenging. The BDI (Belief-Desire-Intention) agent architecture provides a model for building agents that addresses that issue. The model can be used to build intentional agents that are able to reason based on explicit mental attitudes, while behaving reactively in changing circumstances. However, despite the reactive and deliberative features, a classical BDI agent is not capable of learning. Plans as recipes that guide the activities of the agent are assumed to be static. …
Cognitive And Behavioral Model Ensembles For Autonomous Virtual Characters, Jeffrey S. Whiting
Cognitive And Behavioral Model Ensembles For Autonomous Virtual Characters, Jeffrey S. Whiting
Theses and Dissertations
Cognitive and behavioral models have become popular methods to create autonomous self-animating characters. Creating these models presents the following challenges: (1) Creating a cognitive or behavioral model is a time intensive and complex process that must be done by an expert programmer (2) The models are created to solve a specific problem in a given environment and because of their specific nature cannot be easily reused. Combining existing models together would allow an animator, without the need of a programmer, to create new characters in less time and would be able to leverage each model's strengths to increase the character's …
A Dynamic Workflow Framework For Mass Customization Using Web Service And Autonomous Agent Technologies, Daniel J. Karpowitz
A Dynamic Workflow Framework For Mass Customization Using Web Service And Autonomous Agent Technologies, Daniel J. Karpowitz
Theses and Dissertations
Custom software development and maintenance is one of the key expenses associated with developing automated systems for mass customization. This paper presents a method for reducing the risk associated with this expense by developing a flexible environment for determining and executing dynamic workflow paths. Strategies for developing an autonomous agent-based framework and for identifying and creating web services for specific process tasks are presented. The proposed methods are outlined in two different case studies to illustrate the approach for both a generic process with complex workflow paths and a more specific sequential engineering process.
Swarm Intelligence: Theoretical Proof That Empirical Techniques Are Optimal, Dmitry Iourinskiy, Scott A. Starks, Vladik Kreinovich, Stephen F. Smith
Swarm Intelligence: Theoretical Proof That Empirical Techniques Are Optimal, Dmitry Iourinskiy, Scott A. Starks, Vladik Kreinovich, Stephen F. Smith
Departmental Technical Reports (CS)
A natural way to distribute tasks between autonomous agents is to use swarm intelligence techniques, which simulate the way social insects (such as wasps) distribute tasks between themselves. In this paper, we theoretically prove that the corresponding successful biologically inspired formulas are indeed statistically optimal (in some reasonable sense).
Improving And Extending Behavioral Animation Through Machine Learning, Jonathan J. Dinerstein
Improving And Extending Behavioral Animation Through Machine Learning, Jonathan J. Dinerstein
Theses and Dissertations
Behavioral animation has become popular for creating virtual characters that are autonomous agents and thus self-animating. This is useful for lessening the workload of human animators, populating virtual environments with interactive agents, etc. Unfortunately, current behavioral animation techniques suffer from three key problems: (1) deliberative behavioral models (i.e., cognitive models) are slow to execute; (2) interactive virtual characters cannot adapt online due to interaction with a human user; (3) programming of behavioral models is a difficult and time-intensive process. This dissertation presents a collection of papers that seek to overcome each of these problems. Specifically, these issues are alleviated …
Fast And Robust Incremental Action Prediction For Interactive Agents, Jonathan Dinerstein, Parris K. Egbert, Dan A. Ventura
Fast And Robust Incremental Action Prediction For Interactive Agents, Jonathan Dinerstein, Parris K. Egbert, Dan A. Ventura
Faculty Publications
The ability for a given agent to adapt on-line to better interact with another agent is a difficult and important problem. This problem becomes even more difficult when the agent to interact with is a human, since humans learn quickly and behave non-deterministically. In this paper we present a novel method whereby an agent can incrementally learn to predict the actions of another agent (even a human), and thereby can learn to better interact with that agent. We take a case-based approach, where the behavior of the other agent is learned in the form of state-action pairs. We generalize these …
Dawn: A Platform For Evaluating Water-Pricing Policies Using A Software Agent Society, Ioannis N. Athanasiadis, P. Vartalas, P. A. Mitkas
Dawn: A Platform For Evaluating Water-Pricing Policies Using A Software Agent Society, Ioannis N. Athanasiadis, P. Vartalas, P. A. Mitkas
International Congress on Environmental Modelling and Software
Lately there is a transition in water management: policy makers leave aside traditional methods focused on additional-supply policies and focus on water conservation using demand control methods. Water Agencies use water-pricing policies as an instrument for controlling residential water demand. However, design and evaluation of a water-pricing policy is a complex task, as economic, social and political constraints have to be incorporated. In order to support policy makers in their tasks, we developed DAWN, a software tool for evaluating water-pricing policies, implemented as a multi-agent system. DAWN simulates the residential water demand-supply chain and enables the design, creation, modification and …
U.S. Graduate Student Travel To The Second Agentlink European Agent Systems Summer School (Easss) 2000, Thomas A. Wagner
U.S. Graduate Student Travel To The Second Agentlink European Agent Systems Summer School (Easss) 2000, Thomas A. Wagner
University of Maine Office of Research Administration: Grant Reports
This award supports international travel for fifteen U.S. graduate students who would not otherwise be able to attend the Second AgentLink European Agent Systems Summer School being held in Saarbrucken, Germany, from August 14-18, 2000. AgentLink, Europe's ESPRIT-funded Network of Excellence for agent-based computing, organizes the school (http://www.agentlink.org). It is a world-class event that will bring together internationally recognized researchers in the area of autonomous agents and multi-agent systems to present introductory and advanced courses in the theoretical and practical aspects of agent-based computing. The objective of this award is to encourage and enable U.S. graduate students of outstanding merit …
Absolute Bounds On The Mean Of Sum, Product, Max, And Min: A Probabilistic Extension Of Interval Arithmetic, Scott Ferson, Lev Ginzburg, Vladik Kreinovich, Jorge Lopez
Absolute Bounds On The Mean Of Sum, Product, Max, And Min: A Probabilistic Extension Of Interval Arithmetic, Scott Ferson, Lev Ginzburg, Vladik Kreinovich, Jorge Lopez
Departmental Technical Reports (CS)
We extend the main formulas of interval arithmetic for different arithmetic operations x1*x2 to the case when, for each input xi, in addition to the interval [xi]=[xi-,xi+] of possible values, we also know its mean Ei (or an interval [Ei] of possible values of the mean), and we want to find the corresponding bounds for x1*x2 and its mean.