Abstract
Systems that pursue their own goals in shared environments can indirectly affect one another in unanticipated ways, such that the actions of other systems can interfere with goal-achievement. As humans have evolved to achieve goals despite interference from others in society, we thus endow socially situated agents with the capacity for social action as a means of mitigating interference in co-existing systems. We demonstrate that behavioural and evolutionary volatility caused by indirect interactions of goal-rational agents can be reduced by designing agents in a more socially-sensitive manner. We therefore challenge the assumption that designers of intelligent systems typically make, that goal-rationality is sufficient for achieving goals in shared environments.
BibTeX (Download)
@article{Barnes2020BeyondAgents, title = {Beyond Goal-Rationality: Traditional Action Can Reduce Volatility in Socially Situated Agents}, author = {Chloe M. Barnes and Anikó Ekárt and Peter R. Lewis}, url = {https://www.sciencedirect.com/science/article/pii/S0167739X20304714}, doi = {10.1016/j.future.2020.07.033}, year = {2020}, date = {2020-12-01}, urldate = {2020-01-01}, journal = {Future Generation Computer Systems}, volume = {113}, pages = {579--596}, abstract = {Systems that pursue their own goals in shared environments can indirectly affect one another in unanticipated ways, such that the actions of other systems can interfere with goal-achievement. As humans have evolved to achieve goals despite interference from others in society, we thus endow socially situated agents with the capacity for social action as a means of mitigating interference in co-existing systems. We demonstrate that behavioural and evolutionary volatility caused by indirect interactions of goal-rational agents can be reduced by designing agents in a more socially-sensitive manner. We therefore challenge the assumption that designers of intelligent systems typically make, that goal-rationality is sufficient for achieving goals in shared environments.}, keywords = {Agent-Based Systems, ANNs, Artificial Life, Evolutionary Volatility, Neuroevolution, River Crossing, Social Action}, pubstate = {published}, tppubtype = {article} }