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IROS
2006
IEEE
121views Robotics» more  IROS 2006»
14 years 1 months ago
Planning and Acting in Uncertain Environments using Probabilistic Inference
— An important problem in robotics is planning and selecting actions for goal-directed behavior in noisy uncertain environments. The problem is typically addressed within the fra...
Deepak Verma, Rajesh P. N. Rao
DALT
2008
Springer
13 years 9 months ago
Mental State Abduction of BDI-Based Agents
In this paper we present mental state abduction, a technique for inferring the mental states (beliefs, goals) of BDI-based agents from observations of their actions. Abduced mental...
Michal P. Sindlar, Mehdi Dastani, Frank Dignum, Jo...
UAI
2008
13 years 9 months ago
Sampling First Order Logical Particles
Approximate inference in dynamic systems is the problem of estimating the state of the system given a sequence of actions and partial observations. High precision estimation is fu...
Hannaneh Hajishirzi, Eyal Amir
NN
2002
Springer
113views Neural Networks» more  NN 2002»
13 years 7 months ago
Control of exploitation-exploration meta-parameter in reinforcement learning
In reinforcement learning (RL), the duality between exploitation and exploration has long been an important issue. This paper presents a new method that controls the balance betwe...
Shin Ishii, Wako Yoshida, Junichiro Yoshimoto
APIN
2004
81views more  APIN 2004»
13 years 7 months ago
Learning Generalized Policies from Planning Examples Using Concept Languages
In this paper we are concerned with the problem of learning how to solve planning problems in one domain given a number of solved instances. This problem is formulated as the probl...
Mario Martin, Hector Geffner