Game-theoretic Simulations with Cognitive Agents. / Shahid, Nausheen; O'Keeffe, Dan; Stathis, Kostas.

The 33rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI). IEEE Computer Society, 2021.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Forthcoming

Standard

Game-theoretic Simulations with Cognitive Agents. / Shahid, Nausheen; O'Keeffe, Dan; Stathis, Kostas.

The 33rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI). IEEE Computer Society, 2021.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Shahid, N, O'Keeffe, D & Stathis, K 2021, Game-theoretic Simulations with Cognitive Agents. in The 33rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI). IEEE Computer Society.

APA

Shahid, N., O'Keeffe, D., & Stathis, K. (Accepted/In press). Game-theoretic Simulations with Cognitive Agents. In The 33rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI) IEEE Computer Society.

Vancouver

Shahid N, O'Keeffe D, Stathis K. Game-theoretic Simulations with Cognitive Agents. In The 33rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI). IEEE Computer Society. 2021

Author

Shahid, Nausheen ; O'Keeffe, Dan ; Stathis, Kostas. / Game-theoretic Simulations with Cognitive Agents. The 33rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI). IEEE Computer Society, 2021.

BibTeX

@inproceedings{240be38152204b67bc63a6cabb40e0d4,
title = "Game-theoretic Simulations with Cognitive Agents",
abstract = "We propose a novel knowledge representation framework called COGNISIM that supports game theoretic simulation experiments using cognitive agents. The framework allows an experimenter to evolve a population of such agents with strategies expressed teleo-reactively as logic programs. When agents encounter each other, events take place in the environment, caused either by agent actions or by environment processes. Such events change the environment's internal state, and these changes are then observed by agents that, in turn, decide to take new actions that affect the environment. This loop continues until the terminating conditions of the simulation are met. Using this framework, we show how to repeat experiments from the literature based on Axelrod's tournament. We also evaluate our platform's performance in efficiently supporting large simulations in game theoretic settings.",
author = "Nausheen Shahid and Dan O'Keeffe and Kostas Stathis",
year = "2021",
month = sep,
day = "11",
language = "English",
booktitle = "The 33rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI)",
publisher = "IEEE Computer Society",

}

RIS

TY - GEN

T1 - Game-theoretic Simulations with Cognitive Agents

AU - Shahid, Nausheen

AU - O'Keeffe, Dan

AU - Stathis, Kostas

PY - 2021/9/11

Y1 - 2021/9/11

N2 - We propose a novel knowledge representation framework called COGNISIM that supports game theoretic simulation experiments using cognitive agents. The framework allows an experimenter to evolve a population of such agents with strategies expressed teleo-reactively as logic programs. When agents encounter each other, events take place in the environment, caused either by agent actions or by environment processes. Such events change the environment's internal state, and these changes are then observed by agents that, in turn, decide to take new actions that affect the environment. This loop continues until the terminating conditions of the simulation are met. Using this framework, we show how to repeat experiments from the literature based on Axelrod's tournament. We also evaluate our platform's performance in efficiently supporting large simulations in game theoretic settings.

AB - We propose a novel knowledge representation framework called COGNISIM that supports game theoretic simulation experiments using cognitive agents. The framework allows an experimenter to evolve a population of such agents with strategies expressed teleo-reactively as logic programs. When agents encounter each other, events take place in the environment, caused either by agent actions or by environment processes. Such events change the environment's internal state, and these changes are then observed by agents that, in turn, decide to take new actions that affect the environment. This loop continues until the terminating conditions of the simulation are met. Using this framework, we show how to repeat experiments from the literature based on Axelrod's tournament. We also evaluate our platform's performance in efficiently supporting large simulations in game theoretic settings.

M3 - Conference contribution

BT - The 33rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

PB - IEEE Computer Society

ER -