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Evolving Behaviour-Dependent Strategies in Agent Negotiations

Evolving Behaviour-Dependent Strategies in Agent Negotiations
Evolving Behaviour-Dependent Strategies in Agent Negotiations
We use genetic algorithms to evolve trading strategies for iterative bilateral negotiations between buyers and sellers. In contrast to previous work we evolve purely reactive strategies that base decisions on memories of behaviour in previous negotiation rounds. We find that simulations lead to three main types of behaviour: (i) cooperative outcomes in which bargaining leads to an agreement and equal sharing of profits, (ii) uncooperative outcomes in which negotiations are not successful and (iii) outcomes in which one party profits at the expense of the other. The frequencies of each type of behaviour vary when the probability for negotiations to terminate is changed, confirming our hypothesis that cooperation should decrease as this break-off probability increases. Comparisons of the results to tit-for-tat (TFT) strategies and previous research on the iterated prisoner's dilemma (IPD) are used to understand simulation results, and we observe the emergence of TFT behaviour during periods of agent cooperation.
593-600
Falahat, Darius P.
9dd9e809-36dd-439d-8b85-801ed68ab7be
Gerding, Enrico H.
d9e92ee5-1a8c-4467-a689-8363e7743362
Brede, Markus
bbd03865-8e0b-4372-b9d7-cd549631f3f7
Falahat, Darius P.
9dd9e809-36dd-439d-8b85-801ed68ab7be
Gerding, Enrico H.
d9e92ee5-1a8c-4467-a689-8363e7743362
Brede, Markus
bbd03865-8e0b-4372-b9d7-cd549631f3f7

Falahat, Darius P., Gerding, Enrico H. and Brede, Markus (2013) Evolving Behaviour-Dependent Strategies in Agent Negotiations. 12th European Conference on Artificial Life (ECAL 2013), Taormina, Italy. 01 - 05 Sep 2013. pp. 593-600 . (doi:10.7551/978-0-262-31709-2-ch085).

Record type: Conference or Workshop Item (Paper)

Abstract

We use genetic algorithms to evolve trading strategies for iterative bilateral negotiations between buyers and sellers. In contrast to previous work we evolve purely reactive strategies that base decisions on memories of behaviour in previous negotiation rounds. We find that simulations lead to three main types of behaviour: (i) cooperative outcomes in which bargaining leads to an agreement and equal sharing of profits, (ii) uncooperative outcomes in which negotiations are not successful and (iii) outcomes in which one party profits at the expense of the other. The frequencies of each type of behaviour vary when the probability for negotiations to terminate is changed, confirming our hypothesis that cooperation should decrease as this break-off probability increases. Comparisons of the results to tit-for-tat (TFT) strategies and previous research on the iterated prisoner's dilemma (IPD) are used to understand simulation results, and we observe the emergence of TFT behaviour during periods of agent cooperation.

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More information

Published date: 2 September 2013
Venue - Dates: 12th European Conference on Artificial Life (ECAL 2013), Taormina, Italy, 2013-09-01 - 2013-09-05
Organisations: Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 364839
URI: http://eprints.soton.ac.uk/id/eprint/364839
PURE UUID: 6f42fd5c-56e3-41ec-ae45-3133ca2c32f4
ORCID for Enrico H. Gerding: ORCID iD orcid.org/0000-0001-7200-552X

Catalogue record

Date deposited: 12 May 2014 12:20
Last modified: 10 Jul 2020 00:29

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