scholarly journals Colored Multi-Agent Path Finding: Solving Approaches

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Roman Barták ◽  
Marika Ivanová ◽  
Jiří Švancara
Keyword(s):  
Lower Bounds ◽  
Network Flows ◽  
Boolean Satisfiability ◽  
Shared Environment ◽  
Relaxation Techniques ◽  
Path Finding ◽  
Optimal Solutions ◽  
Extended Version ◽  
Continuous Relaxation ◽  
Multi Agent

Multi-Agent Path Finding (MAPF) deals with the problem of finding collision-free paths for a set of agents moving in a shared environment while each agent has specified its destination. Colored MAPF generalizes MAPF by defining groups of agents that share a set of destination locations. In the paper, we evaluate several approaches to optimally solve the colored MAPF problem, namely, a method based on network flows, an extended version of conflict-based search, and two models using Boolean satisfiability. We also investigate methods for obtaining lower bounds on optimal solutions based on constraint and continuous relaxation techniques.

scholarly journals Multi-Agent Path Finding with Deadlines

2018 ◽  
Author(s):  
Hang Ma ◽  
Glenn Wagner ◽  
Ariel Felner ◽  
Jiaoyang Li ◽  
T. K. Satish Kumar ◽  
...  
Keyword(s):  
Flow Problem ◽  
Search Algorithms ◽  
The Other ◽  
Path Finding ◽  
Combinatorial Search ◽  
Programming Formulation ◽  
Commodity Flow ◽  
Linear Programming Formulation ◽  
Multi Agent ◽  
Integer Linear Programming Formulation

We formalize Multi-Agent Path Finding with Deadlines (MAPF-DL). The objective is to maximize the number of agents that can reach their given goal vertices from their given start vertices within the deadline, without colliding with each other. We first show that MAPF-DL is NP-hard to solve optimally. We then present two classes of optimal algorithms, one based on a reduction of MAPF-DL to a flow problem and a subsequent compact integer linear programming formulation of the resulting reduced abstracted multi-commodity flow network and the other one based on novel combinatorial search algorithms. Our empirical results demonstrate that these MAPF-DL solvers scale well and each one dominates the other ones in different scenarios.

Cyber Security Model of Artificial Social System Man-Machine

2015 ◽  
pp. 500-514
Author(s):  
Calin Ciufudean
Keyword(s):  
Cyber Security ◽  
Social System ◽  
Social Systems ◽  
Discrete Event ◽  
Shared Environment ◽  
Security Model ◽  
Automatic Data ◽  
Optimum Trajectory ◽  
Multi Agent ◽  
And Control

Cyber Security Model of Artificial Social System Man-Machine takes advantage of an important chapter of artificial intelligence, discrete event systems applied for modelling and simulation of control, logistic supply, chart positioning, and optimum trajectory planning of artificial social systems. “An artificial social system is a set of restrictions on agents` behaviours in a multi-agent environment. Its role is to allow agents to coexist in a shared environment and pursue their respective goals in the presence of other agents” (Moses & Tennenholtz, n.d.). Despite conventional approaches, Cyber Security Model of Artificial Social System Man-Machine is not guided by rigid control algorithms but by flexible, event-adaptable ones that makes them more lively and available. All these allow a new design of artificial social systems dotted with intelligence, autonomous decision-making capabilities, and self-diagnosing properties. Heuristics techniques, data mining planning activities, scheduling algorithms, automatic data identification, processing, and control represent as many trumps for these new systems analyzing formalism. The authors challenge these frameworks to model and simulate the interaction of man-machine in order to have a better look at the human, social, and organizational privacy and information protection.

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