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» Quantitative Models and Implicit Complexity
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IJCAI
2001
13 years 9 months ago
Complexity of Probabilistic Planning under Average Rewards
A general and expressive model of sequential decision making under uncertainty is provided by the Markov decision processes (MDPs) framework. Complex applications with very large ...
Jussi Rintanen
COCO
2010
Springer
153views Algorithms» more  COCO 2010»
13 years 11 months ago
Communication Complexity with Synchronized Clocks
Abstract—We consider two natural extensions of the communication complexity model that are inspired by distributed computing. In both models, two parties are equipped with synchr...
Russell Impagliazzo, Ryan Williams
DALT
2007
Springer
14 years 1 months ago
Integrating Agent Models and Dynamical Systems
Agent-based modelling approaches are usually based on logical languages, whereas in many areas dynamical system models based on differential equations are used. This paper shows ho...
Tibor Bosse, Alexei Sharpanskykh, Jan Treur
ATAL
2007
Springer
14 years 1 months ago
A computational characterization of multiagent games with fallacious rewards
Agents engaged in noncooperative interaction may seek to achieve a Nash equilibrium; this requires that agents be aware of others’ rewards. Misinformation about rewards leads to...
Ariel D. Procaccia, Jeffrey S. Rosenschein
SEKE
2010
Springer
13 years 6 months ago
Ontology-Based Test Case Generation For Simulating Complex Production Automation Systems
—The behavior of complex production automation systems is hard to predict, therefore simulation is used to study the likely system behavior. However, in a real-world system many ...
Thomas Moser, Gregor Dürr, Stefan Biffl