Packet Routing in Dynamically Changing Networks: A Reinforcement Learning Approach. - Justin A. Boyan; Michael L. Littman (NIPS, 1993)

Generalization in Reinforcement Learning: Safely Approximating the Value Function. - Justin A. Boyan; Andrew W. Moore 001 (NIPS, 1994)

A Reinforcement Learning Framework for Combinatorial Optimization. - Justin A. Boyan (AAAI/IAAI, Vol. 2, 1996)

Learning Evaluation Functions for Large Acyclic Domains. - Justin A. Boyan; Andrew W. Moore 001 (ICML, 1996)

Using Prediction to Improve Combinatorial Optimization Search. - Justin A. Boyan; Andrew W. Moore 001 (AISTATS, 1997)

Learning Evaluation Functions for Global Optimization and Boolean Satisfiability. - Justin A. Boyan; Andrew W. Moore 001 (AAAI/IAAI, 1998)

Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions. - Andrew W. Moore 001; Jeff G. Schneider; Justin A. Boyan; Mary S. Lee (ICML, 1998)

Value Function Based Production Scheduling. - Jeff G. Schneider; Justin A. Boyan; Andrew W. Moore 001 (ICML, 1998)

Least-Squares Temporal Difference Learning. - Justin A. Boyan (ICML, 1999)

Exact Solutions to Time-Dependent MDPs. - Justin A. Boyan; Michael L. Littman (NIPS, 2000)

Learning Evaluation Functions to Improve Optimization by Local Search. - Justin A. Boyan; Andrew W. Moore 001 (J. Mach. Learn. Res., 2000)

Bid determination in simultaneous actions an agent architecture. - Justin A. Boyan; Amy Greenwald (EC, 2001)

Bidding algorithms for simultaneous auctions. - Amy Greenwald; Justin A. Boyan (EC, 2001)

IMproved results for route planning in stochastic transportation. - Justin A. Boyan; Michael Mitzenmacher (SODA, 2001)

Technical Update: Least-Squares Temporal Difference Learning. - Justin A. Boyan (Mach. Learn., 2002)

Bidding under Uncertainty: Theory and Experiments. - Amy Greenwald; Justin A. Boyan (UAI, 2004)