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)
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)
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 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)
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)
AbsTRACT This chapter introduces and analyses a class of non-linear congestion control algorithms called polynomial congestion control algorithms. These generalize the Additive Increase and Multiplicative Decrease (AIMD) algorithms used for the TCP connections. These algorithms provide additive increase using a polynomial of the inverse of the current(More)
Communication for physically challenged people is indispensable for their day to day activities. This paper presents the hardware design of smart sensors for brain machine interface which is used for acquiring the bio potential signals from three different sensors such as EEG, Eyeball and the Eye blink signals. The design was analyzed and validated using(More)
Interactive dynamic influence diagram (I-DID) is a recognized graphical framework for sequential multiagent decision making under uncertainty. I-DIDs concisely represent the problem of how an individual agent should act in an uncertain environment shared with others of unknown types. I-DIDs face the challenge of solving a large number of models that are(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)