TY - CHAP
T1 - Probationary contracts
T2 - 13th European Conference on Multi-Agent Systems, EUMAS 2015 and 3rd International Conference on Agreement Technologies, AT 2015
AU - Haynes, Chris
AU - Miles, Simon
AU - Luck, Michael
PY - 2016/4/17
Y1 - 2016/4/17
N2 - In human organisations, it is common to subject a new employees to periods of probation for which additional restrictions or oversight apply in order to reduce the consequences of poor recruitment choice. In a similar way, multi-agent organisations may need to employ agents of unknown trustworthiness to perform services defined by contracts (or sets of norms), yet these agents may violate the norms for their own advantage. Here, the risk of employing such agents depends on the agents trustworthiness and the consequences of norm violation. In response, in this paper we propose the use of probationary contracts, generated by adding obligations to standard contracts in order to further constrain agent behaviour. We evaluate our work using agent-based simulations of abstract tasks, and present results showing that using probationary roles reduces the risk of using unknown agents, especially where violating a norm has serious consequences.
AB - In human organisations, it is common to subject a new employees to periods of probation for which additional restrictions or oversight apply in order to reduce the consequences of poor recruitment choice. In a similar way, multi-agent organisations may need to employ agents of unknown trustworthiness to perform services defined by contracts (or sets of norms), yet these agents may violate the norms for their own advantage. Here, the risk of employing such agents depends on the agents trustworthiness and the consequences of norm violation. In response, in this paper we propose the use of probationary contracts, generated by adding obligations to standard contracts in order to further constrain agent behaviour. We evaluate our work using agent-based simulations of abstract tasks, and present results showing that using probationary roles reduces the risk of using unknown agents, especially where violating a norm has serious consequences.
UR - http://www.scopus.com/inward/record.url?scp=84964047756&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-33509-4_1
DO - 10.1007/978-3-319-33509-4_1
M3 - Conference paper
AN - SCOPUS:84964047756
SN - 9783319335087
VL - 9571
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 3
EP - 18
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PB - Springer‐Verlag Berlin Heidelberg
Y2 - 17 December 2015 through 18 December 2015
ER -