{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:04:26Z","timestamp":1760241866140,"version":"build-2065373602"},"reference-count":149,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2018,9,25]],"date-time":"2018-09-25T00:00:00Z","timestamp":1537833600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["MTI"],"abstract":"<jats:p>The context of the work presented in this article is the assessment and automated evaluation of human behaviour. To facilitate this, a formalism is presented which is unambiguous as well as such that it can be implemented and interpreted in an automated manner. In the greater scheme of things, comparable behaviour evaluation requires comparable assessment scenarios and, to this end, computer games are considered as controllable and abstract environments. Within this context, a model for behavioural AI is presented which was designed around the objectives of: (a) being able to play rationally; (b) adhering to formally stated behaviour preferences; and (c) ensuring that very specific circumstances can be forced to arise within a game. The presented work is based on established models from the field of behavioural psychology, formal logic as well as approaches from game theory and related fields. The suggested model for behavioural AI has been used to implement and test a game, as well as AI players that exhibit specific behavioural preferences. The overall aim of this article is to enable the readers to design their own AI implementation, using the formalisms and models they prefer and to a level of complexity they desire.<\/jats:p>","DOI":"10.3390\/mti2040063","type":"journal-article","created":{"date-parts":[[2018,9,26]],"date-time":"2018-09-26T10:39:58Z","timestamp":1537958398000},"page":"63","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Designing Behavioural Artificial Intelligence to Record, Assess and Evaluate Human Behaviour"],"prefix":"10.3390","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1471-5774","authenticated-orcid":false,"given":"Hanno","family":"Hildmann","sequence":"first","affiliation":[{"name":"Department de Ingenier\u00eda de Sistemas y Autom\u00e1tica, Universidad Carlos III de Madrid (UC3M), Av. 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