The complexity of achievement and maintenance problems in agent-based systems

Authors:
Iain A. Stewart
Affiliations:
Department of Computer Science, University of Durham, Durham DH1 3LE, UK
Venue:
Artificial Intelligence
Year:
2003

Citing 11
Cited 0

The complexity of propositional linear temporal logics

Journal of the ACM (JACM)
Structural complexity 2

Structural complexity 2
Temporal and modal logic

Handbook of theoretical computer science (vol. B)
The computational complexity of propositional STRIPS planning

Artificial Intelligence
Computational complexity of planning and approximate planning in the presence of incompleteness

Artificial Intelligence
The computational complexity of boolean and stochastic agent design problems

Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
Decidability and Complexity of Petri Net Problems - An Introduction

Lectures on Petri Nets I: Basic Models, Advances in Petri Nets, the volumes are based on the Advanced Course on Petri Nets
The Computational Complexity of Agent Verification

ATAL '01 Revised Papers from the 8th International Workshop on Intelligent Agents VIII
The Computational Complexity of Agent Design Problems

ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
The computational complexity of probabilistic planning

Journal of Artificial Intelligence Research
Computational complexity of planning with temporal goals

IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1

Quantified Score

Hi-index	0.02

Visualization

Abstract

We completely classify the computational complexity of the basic achievement and maintenance agent design problems in bounded environments when these problems are parameterized by the number of environment states and the number of agent actions. The different problems are P-complete, NP-complete, co-NP-complete or PSPACE-complete (when they are not trivial). We also consider alternative achievement and maintenance agent design problems by allowing longer runs in environments (that is, our environments are bounded but the bounds are more liberal than was the case previously). Again, we obtain a complete classification but so that the different problems are DEXPTIME-complete, NEXPTIME-complete, co-NEXPTIME-complete or NEXPSPACE- complete (when they are not trivial).