Social intelligence has a huge impact on the determination of human behaviour in the society. The use of norms can contribute to advances in this social intelligence by the provision of appropriate behaviour based upon the understanding of social situations. Hence, the domain of virtual characters research has given much attention to take advantage of these characteristics of norms particularly in engineering human-like behaviour. However, a lack of capability in reasoning about norms as well as a lack of norm autonomy in virtual characters have significantly diminished the naturalism in virtual characters behaviour. Within this context, a hybrid approach incorporating social and individual reasoning inspired by socio-cognitive theory is taken into account in this thesis. To this end, we propose DNA 3 , Distributed Norm Aware Agent Architecture, established through the integration of (i) the institution, a normative framework performing the social reasoning, (ii) N-Jason, a (BDI-type) cognitive agent carrying out run-time norm-aware deliberation and (iii) a virtual character in charge of perception and realisation of actions.The institution takes responsibility of (i) analysis of state of external worlds byrecording a sequence of event occurrences observed by multiple virtual agents, (ii) reasoning about situationally appropriate behaviour with an assistance from Answer Set Programming (ASP) solver depending upon the social context virtual characters encounter and (iii) in turn detachment of a new set of norms, more precisely normative consequences of specific actions, to virtual characters. This contributes to the enhancement in the flexibility in specifying and reasoning about social norms subject to changes of social situations. Those detached norms are involved in the reasoning process of in-dividual virtual characters. In here, a norm-aware BDI-type agent, N-Jason, performs a practical reasoning to select a plan to execute between norms and goals. Basically, N-Jason offers a generic norm execution mechanism on top of norm aware deliberation to contribute to the exploitation of run-time norm compliance. The selection of agent behaviour is achieved in the norm-aware deliberation process by intention scheduling with deadlines and priorities. This improves the rationality in the choice of behaviour with taking into account the preference on norms and goals in agent mind by evaluation of the importance and imminence between feasible plans triggered by both norms and goals.The design and simulation of politeness is presented as an evaluation of DNA 3 with respect to the effectiveness and adequacy in modelling virtual characters behaviour. The emphasis in here lies on the capability that is able to exhibit different types of appropriate polite behaviour in response to frequent changes in social situations. This is mainly driven by two main activities: prediction of other participants’ intention is carried out by norm-aware virtual characters whilst the understanding of context and reasoning about relevant social behaviour is performed in normative frameworks. For this purpose, three case studies are provided in this thesis: (i) politeness in navigation of individuals, (ii) politeness in the formation and navigation of groups during a guided tour, and(iii) evacuation model as a politeness in the emergency situation. The evaluation is conducted by measuring: (i) the appropriateness of in response to scenarios (e.g.a number of avoiding collisions) and (ii) the reliability of agent decision making (e.g. a response time in relation to norms with the highest priority and the most urgent).
|Date of Award||8 Jun 2015|
|Supervisor||Julian Padget (Supervisor) & Joanna Bryson (Supervisor)|
- Artificial Intelligence
- Normative Multi agent systems
- Decision Making Architecture