Muthukumaran Chandrasekaran

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We present a novel approach for identifying exact and approximate behavioral equivalence between models of agents. This is significant because both decision making and game play in multiagent settings must contend with behavioral models of other agents in order to predict their actions. One approach that reduces the complexity of the model space is to group(More)
Planning for ad hoc teamwork is challenging because it involves agents collaborating without any prior coordination or communication. The focus is on principled methods for a single agent to cooperate with others. This motivates investigating the ad hoc teamwork problem in the context of individual decision making frameworks. However, individual decision(More)
Interactive dynamic influence diagrams (I-DID) are graphical models for sequential decision making in uncertain settings shared by other agents. Algorithms for solving I-DIDs face the challenge of an exponentially growing space of candidate models ascribed to other agents, over time. Pruning behaviorally equivalent models is one way toward minimizing the(More)
Interactive dynamic influence diagrams (I-DID) are graphical models for sequential decision making in uncertain settings shared by other agents. Algorithms for solving I-DIDs face the challenge of an exponentially growing space of candidate models ascribed to other agents, over time. Pruning the behaviorally equivalent models is one way toward identifying a(More)
BACKGROUND Seaweeds are taxonomically diverse benthic algae, which are rich in bioactive compounds. These compounds have a potential application in medicine. OBJECTIVES The aim of the study was to investigate the bioactive properties of three seaweed samples, Enteromorpha antenna, Enteromorpha linza and Gracilaria corticata were collected from the(More)
Evolutionary computation techniques are being frequently used in the field of robotics to develop controllers for autonomous robots. In this paper, we evaluate the use of Genetic Programming (GP) to evolve a controller that implements an Obstacle Avoidance (OA) behavior in a miniature robot. The GP system generates the OA logic equation offline on a(More)
We present a machine learning technique that recognizes patterns of normal movement, using GPS data and time stamps, to gain the ability to detect regions of time containing abnormal movement. We argue people move throughout regions of time in established patterns, and a person's normal movement can be learned by machines. We use intelligent features(More)
Open agent systems are multiagent systems in which one or more agents may leave the system at any time possibly resuming after some interval and in which new agents may also join. Planning in such systems becomes challenging in the absence of inter-agent communication because agents must predict if others have left the system or new agents are now present(More)
Planning for ad hoc teamwork is challenging because it involves agents collaborating without any prior coordination or communication. The focus is on principled methods for a single agent to cooperate with others. This motivates investigating the ad hoc teamwork problem in the context of self-interested decision-making frameworks. Agents engaged in(More)