Decision making using probabilistic inference methods
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
APRIL—Agent PRocess Interaction Language
ECAI-94 Proceedings of the workshop on agent theories, architectures, and languages on Intelligent agents
Imposing security constraints on agent-based decision support
Decision Support Systems - Special issue: intelligent agents as a basis for decision support systems
Modern Control Engineering
Making a Case for Multi-Agent Systems
Proceedings of the 8th European Workshop on Modelling Autonomous Agents in a Multi-Agent World: Multi-Agent Rationality
Complexity of finite-horizon Markov decision process problems
Journal of the ACM (JACM)
Artificial Agent Action in Markets
Electronic Commerce Research - Special issue on agents in electronic commerce
Multi Agent Based Simulation: Beyond Social Simulation
MABS '00 Proceedings of the Second International Workshop on Multi-Agent-Based Simulation-Revised and Additional Papers
RoboCup-99: Robot Soccer World Cup III
Distributed monitoring and control of office buildings by embedded agents
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Intelligent embedded agents
Intelligent light control using sensor networks
Proceedings of the 3rd international conference on Embedded networked sensor systems
A Multi-Agent System for Building Control
IAT '06 Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology
Distributed monitoring and control of office buildings by embedded agents
Information Sciences: an International Journal
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Our hypothesis is that by equipping certain in a multi-agent system controlling an intelligent building with automated decision support, two important factors will be increased. The first is energy saving in the building. The second is customer value-how the people in the building experience the effects of the actions of the agents. We give evidence for the truth of this hypothesis through experimental findings related to tools for artificial decision making. A number of assumptions related to agent control, through monitoring and delegation of tasks to other kinds of agents, of rooms at a test site are relaxed. Each assumption controls at least one uncertainty that complicates considerably the procedures for selecting actions part of each such agent. We show that in realistic decision situations, room-controlling agents can make bounded rational decisions even under dynamic real-time constraints. This result can be, and has been, generalized to other domains with even harsher time constraints.