Learning for Search

Papers from the 2006 AAAI Workshop

Wheeler Ruml and Frank Hutter, Program Cochairs

Technical Report WS-06-11 published by The AAAI Press, Menlo Park, California

This technical report is also available in book and CD format.

Please Note: Abstracts are linked to individual titles, and will appear in a separate browser window. Full-text versions of the papers are linked to the abstract text. Access to full text may be restricted to AAAI members. PDF file sizes may be large!

Preface / vii
Wheeler Ruml and Frank Hutter

Organizing Committee / vii
Wheeler Ruml and Frank Hutter

Oral Presentations

The Effect of Restarts on the Efficiency of Clause Learning / 1
Jinbo Huang

Learning from Failure in Constraint Satisfaction Search / 7
Diarmuid Grimes and Richard J.Wallace

Disco — Novo — GoGo: Integrating Local Search and Complete Search with Restarts / 15
Meinolf Sellmann and Carlos Ans&oactue;tegui

Estimating Search Tree Size / 21
Philip Kilby, John Slaney, Sylvie Thiébaux, and Toby Walsh

Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms: An Initial Investigation / 28
Frank Hutter, Youssef Hamadi, Holger H. Hoos, and Kevin Leyton-Brown

Toward Discriminative Learning of Planning Heuristics / 35
Yuehua Xu and Alan Fern

Prioritized-LRTA*: Speeding Up Learning via Prioritized Updates / 43
D. Chris Rayner, Katherine Davison, Vadim Bulitko, and Jieshan Lu

PAC Reinforcement Learning Bounds for RTDP and Rand-RTDP / 50
Alexander L. Strehl, Lihong Li, and Michael L. Littman

Real-Time Adaptive A* / 57
Sven Koenig and Maxim Likhachev

Poster Presentations

Storing Learnt (No)Goods in ROBDDs for Solving Structured CSPs / 65
Karim Boutaleb, Philippe Jégou, and Cyril Terrioux

State Abstraction for Real-time Moving Target Pursuit: A Pilot Study / 72
Vadim Bulitko and Nathan Sturtevant

Replaying Types Sequences in Forward Heuristic Planning / 80
Tomás de la Rosa, Daniel Borrajo, and Angel García Olaya

Transfer of Learned Heuristics Among Planners / 85
Susana Fernández, Ricardo Aler, and Daniel Borrajo

Some Active Learning Schemes to Acquire Control Knowledge for Planning / 93
Raquel Fuentetaja and Daniel Borrajo

nLRTS: Improving Distance Vector Routing in Sensor Networks / 101
Greg Lee, Vadim Bulitko, and Ioanis Nikolaidis

Lookahead Pathology in Real-Time Path-Finding / 108
Mitja Lustrek and Vadim Bulitko

Relative Support Weight Learning for Constraint Solving / 115
Smiljana Petrovic and Susan Epstein

An Empirical Evaluation of Automated Knowledge Discovery in a Complex Domain / 123
Jay H. Powell and John D. Hastings

Directing a Portfolio with Learning / 129
Mark Roberts and Adele E. Howe

Value Back-Propagation versus Backtracking in Real-Time Heuristic Search / 136
Sverrir Sigmundarson and Yngvi Björnsson

Discrepancy Search with Reactive Policies for Planning / 142
Sungwook Yoon

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