Tracking and data association
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
The CDP: A unifying formulation for heuristic search, dynamic programming, and branch-and-bound
Search in Artificial Intelligence
Abductive inference models for diagnostic problem-solving
Abductive inference models for diagnostic problem-solving
Cost-based abduction and MAP explanation
Artificial Intelligence
Finding MAPs for belief networks is NP-hard
Artificial Intelligence
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Predicting tradeoffs in contract-based distributed scheduling
Predicting tradeoffs in contract-based distributed scheduling
A framework for the analysis of sophisticated control
A framework for the analysis of sophisticated control
A Framework for the Analysis of Sophisticated Control in Interpretation Systems
A Framework for the Analysis of Sophisticated Control in Interpretation Systems
Nearly monotonic problems: a key to effective FA/C distributed sensor interpretation?
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Minimizing communication cost in a distributed Bayesian network using a decentralized MDP
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Analyzing the efficiency of strategies for MAS-based sensor interpretation and diagnosis
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Diagnosis of single and multi-agent plans
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Communication management using abstraction in distributed bayesian networks
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Communication management using abstraction in distributed Bayesian networks
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
On-line monitoring of plan execution: A distributed approach
Knowledge-Based Systems
Supervision and diagnosis of joint actions in multi-agent plans
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Using DESs for Temporal Diagnosis of Multi-agent Plan Execution
MATES '07 Proceedings of the 5th German conference on Multiagent System Technologies
Diagnosis of Plan Structure Violations
MATES '07 Proceedings of the 5th German conference on Multiagent System Technologies
Team Cooperation for Plan Recovery in Multi-agent Systems
MATES '07 Proceedings of the 5th German conference on Multiagent System Technologies
Plan Diagnosis and Agent Diagnosis in Multi-agent Systems
AI*IA '07 Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing
Finding Minimum Data Requirements Using Pseudo-independence
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Primary and secondary diagnosis of multi-agent plan execution
Autonomous Agents and Multi-Agent Systems
Models and methods for plan diagnosis
Autonomous Agents and Multi-Agent Systems
Diagnosis of Simple Temporal Networks
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Performance evaluation of DPS coordination strategies modelled in pi-calculus
International Journal of Intelligent Information and Database Systems
Diagnosis of plan execution and the executing agent
KI'05 Proceedings of the 28th annual German conference on Advances in Artificial Intelligence
CEEMAS'05 Proceedings of the 4th international Central and Eastern European conference on Multi-Agent Systems and Applications
Diagnosis of multi-agent plan execution
MATES'06 Proceedings of the 4th German conference on Multiagent System Technologies
Deadlock verification of a DPS coordination strategy and its alternative model in pi-calculus
International Journal of Intelligent Information and Database Systems
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The growth in computer networks has created the potential to harness a great deal of computing power, but new models of distributed computing are often required. Cooperative distributed problem solving (CDPS) is the subfield of multi-agent systems (MAS) that is concerned with how large-scale problems can be solved using a network of intelligent agents working together. Building CDPS systems for real-world applications is still very difficult, however, in large part because the effects that domain and strategy characteristics have on the performance of CDPS systems are not well understood. This paper reports on the first results from a new simulation-based analysis system that has been created to study the performance of CDPS-based distributed sensor interpretation (DSI) and distributed diagnosis (DD). To demonstrate the kind of results that can be obtained, we have investigated how the monotonicity of a domain affects the performance of a potentially very efficient class of strategies for CDPS-based DSI/DD. Local solutions strategies attempt to limit communications among the agents by focusing on using the agents' local solutions to produce global solutions. While these strategies have been described as being important for effective CDPS-based DSI/DD, they need not perform well if a domain is nonmonotonic. We had previously suggested that the reason they have performed well in several research systems was that many DSI/DD domains are what we termed nearly monotonic. In this paper, we will provide quantitative results that relate the performance of local solutions strategies to the monotonicity of a domain. The experiments confirm that domain monotonicity can be important to consider, but they also show that it is possible for these strategies to be effective even when domains are relatively nonmonotonic. What is required is that the agents receive a significant fraction of the data that is relevant to their subproblems. This has important implications for the design of DSI/DD systems using local solutions strategies. In addition, while the work indicates that many DSI/DD domains are likely to be “nearly monotonic” according to our original definitions, it also shows that these measures are not as predictive of performance as other measures we define. This means that near monotonicity alone does not explain why local solutions strategies have performed well in previous systems. Instead, a likely explanation is that these systems typically involved only a small number of agents.