- Recursive Sparse, Spatiotemporal Coding Thomas Dean
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- A Decision-Theoretic Approach to Planning, Perception and Control
- Bounded-parameter Markov Decision Processes, June 16, 2000 1 Bounded-parameter Markov Decision Processes
- Decision-Theoretic Deliberation Scheduling for Problem Solving in Time-Constrained Environments
- Learning Dynamics: System Identi cation for Perceptually Challenged Agents
- A Computational Model of the Cerebral Cortex Thomas Dean
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- Revised submission to Artificial Intelligence special issue on Planning and Scheduling ! " # $ % & ' $ ( ) 0 ' % 1 2 ' 3 $ 4 5 6 $ ' 1 7 1 2 ( 8 ) 9 $ 5 6 2 @ # $ ( ) A ( ( B 2 4 ! " 1 % " (
- Solving Very Large Weakly Coupled Markov Decision Processes Nicolas Meuleau, Milos Hauskrecht,
- Exploiting Locality in Searching the Web Joel Young Thomas Dean
- Coping With Uncertainty in Map Learning Kenneth Basye Thomas Dean Je rey Scott Vittery
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- Journal of Arti cial Intelligence Research 11 (1999) 1{94 Submitted 09/98 published 07/99 Decision-Theoretic Planning: Structural Assumptions and
- 574 IEEE TRANSACTIONS ON SYSTEMS. MAN, ANI) CYBERNETICS. VOI.. 19. NO. 3, MAY/JIJNE 1989 Persistence and Probabilistic Projection
- Scalable Inference in Hierarchical Generative Models Thomas Dean
- Coping With Uncertainty in Map Learning Kenneth Basye Thomas Dean Je rey Scott Vittery
- On the Prospects for Building a Working Model of the Visual Cortex Thomas Dean
- Solving Factored MDPs via Non-Homogeneous Partitioning Kee-Eung Kim and Thomas Dean
- Approximate Solutions to Factored Markov Decision Processes via Greedy Search in the Space of Finite State Controllers
- Learning Invariant Features Using Inertial Thomas Dean
- ! " # $ % & # ' ( ) 0 1 2 ! 3 & 4 5 6 7 8 # ' 9 @ A B C D E @ F D G H I G E A P D @ C Q R S@ F R @
- Reinforcement Learning for Planning and Control
- Equivalence Notions and Model Minimization in Markov Decision Processes
- Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning
- A Framework for the Development of Multi-Agent Architectures
- Using Temporal Hierarchies to Efficiently Maintain Large Temporal Databases
- Solving Stochastic Planning Problems With Large State and Action Spaces Thomas Dean, Robert Givan, and Kee-Eung Kim
