Massachusetts Institute of Technology 16.412/6.834 Cognitive Robotics Distributed: Monday, 3/31/04 Objective The purpose of the following handout is to walk you step by step through the execution of the FF planning algorithm, on a simple example. The FF algorithm is presented in the paper:

Distributed constraint Satisfaction problems 2 Asynchronous algorithms Thomas leaute 16.412J-Cognitive Robotics april 7. 2004 Presentation outline Introduction to CSPs and DCSPs 2. The Asynchronous Backtracking Algorithm 3. The asynchronous Weak-Commitment Search algorithm 4. Conclusion and Introduction to the task Allocation problem M. Yokoo, E Durfee, T. Ishida and K. Kuwabara, Distributed Constraint Satisfa

Cognitive Robotics Outline Temporal Action Graph Walksat: Stochastic Local Search Better Neighbor Relaxed Plan A. Gerevini, A. Saetti, I. Serina \Planning through Stochastic Local Search and Temporal Action Graphs\, to appear in Journal of Artificial Intelligence

Fast Solutions to CSPs Presented by: Robert Effinger Dan Lovell Presented To: 16.412J Cognitive Robotics MIT References: \Dynamic Backtracking\ Matthew L. Ginsberg, CIRL, University of Oregon Journal of Artificial Intelligence Research 1(1993)

Readings in Planning as Forward Heuristic Search \The FF Planning System: Fast Plan Generation Through Heuristic Search,\ by Jorg Hoffmann and Bernhard Nebel, Journal of Artificial Intelligence Research, 2001. “Planning as Heuristic Search,\ by Blai Bonet and Hector Geffner, Artificial

Using the Forest to See the Trees: Context-based Object Recognition Bill Freeman Joint work with Antonio Torralba and Kevin Murphy Computer Science and Artificial Intelligence Laboratory MIT computer vision goal Recognize many different objects under many viewing conditions in unconstrained settings

Hybrid Mode Estimation and Gaussian Filtering with Hybrid HMMs Stanislav funiak 16. 412/6.834 Lecture, 15 March 2004 References Hofbaur, M. W, and Williams, B C(2002). Mode estimation of probabilistic hybrid systems. In: Hybrid Systems: Computation and Control Hscc 2002 Funiak, S, and Williams, B. C (2003 ). Multi-modal particle filtering for hybrid systems with autonomous mode transitions. In: DX-2003 SafeProcess 2003 Lerner, U.,R. Parr, D. Koller and G. Biswas(2000). Bayesian fault detection and diagnosis in dynamic

Model-based Diagnosis a failure is a discrepancy between the model and observations of an artifact a diagnosis restores consistency 1. Enumerate candidates in order of likelihood

Brian C Williams, copyright 2000 Mode estimation Mode reconfiguration Select a most likely set of Select a least cost set of component modes that are commandable component consistent with the model and modes that entail the current observations

Mapping Topics: Topological Maps SLAM HMMs Revisited Additional reading: B. J. Kuipers Y.-T. Byun. 1991. \A robot exploration and mapping strategy based on a semantic hierarchy of spatial rep rstations. jour. s and