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dc.contributor.authorHarris, Chris
dc.date.accessioned2017-10-10T13:08:57Z
dc.date.available2017-10-10T13:08:57Z
dc.date.issued2017-07-20
dc.identifier.isbn9783319641065
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.urihttp://hdl.handle.net/10026.1/10036
dc.description.abstract

© Springer International Publishing AG 2017. On our crowded roads, drivers must compete for space but cooperate to avoid occupying the same space at the same time. Decision-making is strategic and requires mutual understanding of other’s choices. Fully autonomous vehicles (AVs) will need risk management software to make these types strategic decisions without human arbitration. Accidents will occur, and what constitutes rational and ‘safe’ decisions will be scrutinized by the legal system. It is far from clear how AV-Human and AV-AV interactions should be managed. Game Theory provides a framework for analyzing mutual ‘games’ with 2 or more players. It assumes that players mutually optimize their outcomes according to Nash equilibria (NE), but do humans follow Nash equilibria in Human-Human interactions? We implemented simple two-player competitive games to see whether people played rationally according to Nash equilibria. On each of 100 trials, each player was instructed to maximise their reward by pressing one of three buttons labelled “4”, “6”, and “12”, without knowing the other players choice. If players pressed different buttons, they received a reward of 4, 6, or 12 points accordingly. If players pressed the same button, the reward was reduced depending on the game type. Results showed that players did not follow NE, but played a probabilistic game that included the “4” button, even though pressing this button is always suboptimal. We suggest that this may be an evolutionary strategy, but it clearly shows that people do not follow the ‘rational’ Nash strategy. It seems that AV-human interactions will be probabilistic. In AV-AV interactions, software may be playing itself, and may also require probabilistic optimal evolutionary-type strategies. We doubt that the full implications of autonomous decision-making have been fully worked out. Whether probabilistic decisions will tolerated legally and actuarially is doubtful. One way to avoid them would be to allow regulated AV-AV communications, and force software decisions to be deterministic according to some protocol. However, AV-Human interactions seem likely to remain problematic.

dc.format.extent315-324
dc.language.isoen
dc.publisherSpringer International Publishing
dc.subjectRationality
dc.subjectDecision making
dc.subjectNash equilibrium
dc.subjectReward
dc.subjectMatching law
dc.subjectAutonomous agents
dc.subjectEvolutionary game theory
dc.titleAutonomous vehicle decision-making: Should we be bio-inspired?
dc.typeconference
dc.typeConference Proceeding
plymouth.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000453217100025&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008
plymouth.volume10454 LNAI
plymouth.publication-statusPublished
plymouth.journalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.identifier.doi10.1007/978-3-319-64107-2_25
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Health
plymouth.organisational-group/Plymouth/Research Groups
plymouth.organisational-group/Plymouth/Research Groups/Centre for Brain, Cognition and Behaviour (CBCB)
plymouth.organisational-group/Plymouth/Research Groups/Centre for Brain, Cognition and Behaviour (CBCB)/Brain
plymouth.organisational-group/Plymouth/Users by role
dcterms.dateAccepted2017-04-28
dc.identifier.eissn1611-3349
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.1007/978-3-319-64107-2_25
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2017-07-20
rioxxterms.typeConference Paper/Proceeding/Abstract


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