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    AAAI
    2006
    213views Intelligent Agents» more  AAAI 2006»
    A Multi Agent Approach to Vision Based Robot Scavenging
    13 years 5 months ago
    A Multi Agent Approach to Vision Based Robot Scavenging
    Download  www.aaai.org
    This paper proposes a design for our entry into the 2006 AAAI Scavenger Hunt Competition and Robot Exhibition. We will be entering a scalable two agent system consisting of off-th...
    Kamil Wnuk, Brian Fulkerson, Jeremi Sudol
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    AAAI
    2006
    165views Intelligent Agents» more  AAAI 2006»
    Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems
    13 years 5 months ago
    Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems
    Download  www.aaai.org
    The Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent parame...
    David Wingate, Satinder P. Singh
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    AAAI
    2006
    161views Intelligent Agents» more  AAAI 2006»
    Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning
    13 years 5 months ago
    Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning
    Download  staff.science.uva.nl
    Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
    Shimon Whiteson, Peter Stone
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    AAAI
    2006
    134views Intelligent Agents» more  AAAI 2006»
    When Is Constrained Clustering Beneficial, and Why?
    13 years 5 months ago
    When Is Constrained Clustering Beneficial, and Why?
    Download  www.wkiri.com
    Several researchers have illustrated that constraints can improve the results of a variety of clustering algorithms. However, there can be a large variation in this improvement, e...
    Kiri Wagstaff, Sugato Basu, Ian Davidson
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    AAAI
    2006
    125views Intelligent Agents» more  AAAI 2006»
    Trust Representation and Aggregation in a Distributed Agent System
    13 years 5 months ago
    Trust Representation and Aggregation in a Distributed Agent System
    Download  www.csc.ncsu.edu
    This paper considers a distributed system of software agents who cooperate in helping their users to find services, provided by different agents. The agents need to ensure that th...
    Yonghong Wang, Munindar P. Singh
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    AAAI
    2006
    121views Intelligent Agents» more  AAAI 2006»
    Methods for Empirical Game-Theoretic Analysis
    13 years 5 months ago
    Methods for Empirical Game-Theoretic Analysis
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    Michael P. Wellman
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    AAAI
    2006
    142views Intelligent Agents» more  AAAI 2006»
    Evaluating Preference-based Search Tools: A Tale of Two Approaches
    13 years 5 months ago
    Evaluating Preference-based Search Tools: A Tale of Two Approaches
    Download  www.aaai.org
    People frequently use the world-wide web to find their most preferred item among a large range of options. We call this task preference-based search. The most common tool for pref...
    Paolo Viappiani, Boi Faltings, Pearl Pu
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    AAAI
    2006
    112views Intelligent Agents» more  AAAI 2006»
    An Introduction to Nonlinear Dimensionality Reduction by Maximum Variance Unfolding
    13 years 5 months ago
    An Introduction to Nonlinear Dimensionality Reduction by Maximum Variance Unfolding
    Download  cseweb.ucsd.edu
    Kilian Q. Weinberger, Lawrence K. Saul
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    AAAI
    2006
    83views Intelligent Agents» more  AAAI 2006»
    Integrating Clustering and Classification for Estimating Process Variables in Materials Science
    13 years 5 months ago
    Integrating Clustering and Classification for Estimating Process Variables in Materials Science
    Download  web.cs.wpi.edu
    Aparna S. Varde, Elke A. Rundensteiner, Carolina R...
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    AAAI
    2006
    157views Intelligent Agents» more  AAAI 2006»
    Compact, Convex Upper Bound Iteration for Approximate POMDP Planning
    13 years 5 months ago
    Compact, Convex Upper Bound Iteration for Approximate POMDP Planning
    Download  www.aaai.org
    Partially observable Markov decision processes (POMDPs) are an intuitive and general way to model sequential decision making problems under uncertainty. Unfortunately, even approx...
    Tao Wang, Pascal Poupart, Michael H. Bowling, Dale...
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