Adaptive signal processing
Learning automata: an introduction
Learning automata: an introduction
From Chemotaxis to cooperativity: abstract exercises in neuronal learning strategies
The computing neuron
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Practical Issues in Temporal Difference Learning
Machine Learning
A dynamic load balancing approach to the control of multi-server polling systems with applications to elevator system dispatching
TD-Gammon, a self-teaching backgammon program, achieves master-level play
Neural Computation
Learning to act using real-time dynamic programming
Artificial Intelligence - Special volume on computational research on interaction and agency, part 1
Temporal difference learning and TD-Gammon
Communications of the ACM
Some studies in machine learning using the game of checkers
Computers & thought
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Neuro-Dynamic Programming
Advances in Neural Information Processing Systems 5, [NIPS Conference]
Adaptation and Learning in Multi-Agent Systems: Some Remarks and a Bibliography
IJCAI '95 Proceedings of the Workshop on Adaption and Learning in Multi-Agent Systems
A Distributed Reinforcement Learning Scheme for Network Routing
A Distributed Reinforcement Learning Scheme for Network Routing
Large-scale dynamic optimization using teams of reinforcement learning agents
Large-scale dynamic optimization using teams of reinforcement learning agents
Algorithms for sequential decision-making
Algorithms for sequential decision-making
Hierarchical multi-agent reinforcement learning
Proceedings of the fifth international conference on Autonomous agents
Recent Advances in Hierarchical Reinforcement Learning
Discrete Event Dynamic Systems
A Topic-Specific Web Robot Model Based on Restless Bandits
IEEE Internet Computing
Machines that learn to play games
An Architectural Framework for Integrated Multiagent Planning, Reacting, and Learning
ATAL '00 Proceedings of the 7th International Workshop on Intelligent Agents VII. Agent Theories Architectures and Languages
Spatiotemporal Abstraction of Stochastic Sequential Processes
Proceedings of the 5th International Symposium on Abstraction, Reformulation and Approximation
Recent Advances in Hierarchical Reinforcement Learning
Discrete Event Dynamic Systems
Lyapunov design for safe reinforcement learning
The Journal of Machine Learning Research
Learning to Communicate and Act Using Hierarchical Reinforcement Learning
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Coordinating Multiple Agents via Reinforcement Learning
Autonomous Agents and Multi-Agent Systems
Discrete Applied Mathematics - Special issue: Traces of the Latin American conference on combinatorics, graphs and applications: a selection of papers from LACGA 2004, Santiago, Chile
Neural-based downlink scheduling algorithm for broadband wireless networks
Computer Communications
Evolutionary Function Approximation for Reinforcement Learning
The Journal of Machine Learning Research
Empirical Studies in Action Selection with Reinforcement Learning
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Application of reinforcement learning to the game of Othello
Computers and Operations Research
Coordination in multiagent reinforcement learning systems by virtual reinforcement signals
International Journal of Knowledge-based and Intelligent Engineering Systems
Hierarchical Average Reward Reinforcement Learning
The Journal of Machine Learning Research
Reinforcement learning for problems with symmetrical restricted states
Robotics and Autonomous Systems
Sample-efficient evolutionary function approximation for reinforcement learning
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Accelerating reinforcement learning through implicit imitation
Journal of Artificial Intelligence Research
Risk-sensitive reinforcement learning applied to control under constraints
Journal of Artificial Intelligence Research
Natural actor-critic algorithms
Automatica (Journal of IFAC)
Engineering Applications of Artificial Intelligence
Adaptive data-aware utility-based scheduling in resource-constrained systems
Adaptive data-aware utility-based scheduling in resource-constrained systems
RL-Glue: Language-Independent Software for Reinforcement-Learning Experiments
The Journal of Machine Learning Research
Autonomous Agents and Multi-Agent Systems
Extending adaptive fuzzy behavior hierarchies to multiple levels of composite behaviors
Robotics and Autonomous Systems
Adaptive data-aware utility-based scheduling in resource-constrained systems
Journal of Parallel and Distributed Computing
Intelligent negotiation behaviour model for an open railway access market
Expert Systems with Applications: An International Journal
Coordinated learning in multiagent MDPs with infinite state-space
Autonomous Agents and Multi-Agent Systems
Marginalizing out future passengers in group elevator control
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
An efficient control method for elevator group control system
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part II
Structural abstraction experiments in reinforcement learning
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Elevator group control by using talented algorithm
TAINN'05 Proceedings of the 14th Turkish conference on Artificial Intelligence and Neural Networks
Emergent consensus in decentralised systems using collaborative reinforcement learning
Self-star Properties in Complex Information Systems
A distributed learning control system for elevator groups
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
A rapid sparsification method for kernel machines in approximate policy iteration
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Novel method for using Q-learning in small microcontrollers
Proceedings of the 51st ACM Southeast Conference
Reinforcement learning algorithms with function approximation: Recent advances and applications
Information Sciences: an International Journal
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Recent algorithmic and theoretical advances in reinforcement learning (RL) have attracted widespread interest. RL algorithms have appeared that approximate dynamic programming on an incremental basis. They can be trained on the basis of real or simulated experiences, focusing their computation on areas of state space that are actually visited during control, making them computationally tractable on very large problems. If each member of a team of agents employs one of these algorithms, a new collective learning algorithm emerges for the team as a whole. In this paper we demonstrate that such collective RL algorithms can be powerful heuristic methods for addressing large-scale control problems.Elevator group control serves as our testbed. It is a difficult domain posing a combination of challenges not seen in most multi-agent learning research to date. We use a team of RL agents, each of which is responsible for controlling one elevator car. The team receives a global reward signal which appears noisy to each agent due to the effects of the actions of the other agents, the random nature of the arrivals and the incomplete observation of the state. In spite of these complications, we show results that in simulation surpass the best of the heuristic elevator control algorithms of which we are aware. These results demonstrate the power of multi-agent RL on a very large scale stochastic dynamic optimization problem of practical utility.