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...
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...
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...
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...
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...
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...
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...