Artificial Intelligence
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Trading Space for Time in Undirected $s-t$ Connectivity
SIAM Journal on Computing
Emergent coordination through the use of cooperative state-changing rules
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Graph learning with a nearest neighbor approach
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Algorithm 447: efficient algorithms for graph manipulation
Communications of the ACM
Graph Algorithms
Efficient Exploration In Reinforcement Learning
Efficient Exploration In Reinforcement Learning
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Terrain coverage with ant robots: a simulation study
Proceedings of the fifth international conference on Autonomous agents
Cross-entropy and rare events for maximal cut and partition problems
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue: Rare event simulation
Efficient and inefficient ant coverage methods
Annals of Mathematics and Artificial Intelligence
From Ants to A(ge)nts: A Special Issue on Ant-Robotics
Annals of Mathematics and Artificial Intelligence
Spanning-tree based coverage of continuous areas by a mobile robot
Annals of Mathematics and Artificial Intelligence
Coverage for robotics – A survey of recent results
Annals of Mathematics and Artificial Intelligence
Ant Algorithms Solve Difficult Optimization Problems
ECAL '01 Proceedings of the 6th European Conference on Advances in Artificial Life
Towards Building Terrain-Covering Ant Robots
ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
A Comparative Study of ANT-Based Optimization for Dynamic Routing
AMT '01 Proceedings of the 6th International Computer Science Conference on Active Media Technology
Improved approximation algorithms for the freeze-tag problem
Proceedings of the fifteenth annual ACM symposium on Parallel algorithms and architectures
Building Terrain-Covering Ant Robots: A Feasibility Study
Autonomous Robots
Cooperative Cleaners: A Study in Ant Robotics
International Journal of Robotics Research
Robust and Efficient Covering of Unknown Continuous Domains with Simple, Ant-Like A(ge)nts
International Journal of Robotics Research
Ant Focused Crawling Algorithm
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
On redundancy, efficiency, and robustness in coverage for multiple robots
Robotics and Autonomous Systems
Multi-a(ge)nt Graph Patrolling and Partitioning
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Multi-robot area patrol under frequency constraints
Annals of Mathematics and Artificial Intelligence
Autonomous multi-agent cycle based patrolling
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
The complexity of grid coverage by swarm robotics
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Static and expanding grid coverage with ant robots: Complexity results
Theoretical Computer Science
Multi-agent Cooperative Cleaning of Expanding Domains
International Journal of Robotics Research
Covering a continuous domain by distributed, limited robots
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
Route discovery in cellular networks using soft computing techniques
International Journal of Advanced Intelligence Paradigms
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Efficient graph search is a central issue in many aspects of AI. In most of existing work there is a distinction between the active “searcher”, which both executes the algorithm and holds the memory, and the passive “searched graph”, over which the searcher has no control at all. Large dynamic networks like the Internet, where the nodes are powerful computers and the links have narrow bandwidth and are heavily‐loaded, call for a different paradigm, in which most of the burden of computing and memorizing is moved from the searching agent to the nodes of the network. In this paper we suggest a method for searching an undirected, connected graph using the Vertex‐Ant‐Walk method, where an a(ge)nt walks along the edges of a graph G, occasionally leaving “pheromone” traces at nodes, and using those traces to guide its exploration. We show that the ant can cover the graph within time \mathrm{O}(nd), where n is the number of vertices and d the diameter of G. The use of traces achieves a trade‐off between random and self‐avoiding walks, as it dictates a lower priority for already‐visited neighbors. Further properties of the suggested method are: (a) modularity: a group of searching agents, each applying the same protocol, can cooperate on a mission of covering a graph with minimal explicit communication between them; (b) possible convergence to a limit cycle: a Hamiltonian path in G (if one exists) is a possible limit cycle of the process.