This extended abstract summarises the contributions from the journal article Fisher et al.@en

A computational system is called autonomous if it is able to make its own decisions, or take its own actions, without human supervision or control. The capability and spread of such systems have reached the point where they are beginning to touch much of everyday life. However, regulators grapple with how to deal with autonomous systems, for example how could we certify an Unmanned Aerial System for autonomous use in civilian airspace? We here analyse what is needed in order to provide verified reliable behaviour of an autonomous system, analyse what can be done as the state-of-the-art in automated verification, and propose a roadmap towards developing regulatory guidelines, including articulating challenges to researchers, to engineers, and to regulators. Case studies in seven distinct domains illustrate the article.@en

The issue of explainability for autonomous systems is becoming increasingly prominent. Several researchers and organisations have advocated the provision of a “Why did you do that?” button which allows a user to interrogate a robot about its choices and actions. We take previous work on debugging cognitive agent programs and apply it to the question of supplying explanations to end users in the form of answers to why-questions. These previous approaches are based on the generation of a trace of events in the execution of the program and then answering why-questions using the trace. We implemented this framework in the agent infrastructure layer and, in particular, the Gwendolen programming language it supports – extending it in the process to handle the generation of applicable plans and multiple intentions. In order to make the answers to why-questions comprehensible to end users we advocate a two step process in which first a representation of an explanation is created and this is subsequently converted into natural language in a way which abstracts away from some events in the trace and employs application specific predicate dictionaries in order to translate the first-order logic presentation of concepts within the cognitive agent program in natural language. A prototype implementation of these ideas is provided.

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We address the question of how an agent can adapt its behavior to comply with newly adopted norms. This is particularly relevant in the case of open systems where agents may enter and leave norm-governed social contexts not known at design time. This requires norms to be explicitly and separately stated and presented to an agent as rules to which it then can try to adapt its behavior.
We propose a formal semantic framework that specifies an execution mechanism for such socially adaptive agents. This framework is based on expressing norms using Linear Temporal Logic. The formality of the framework allows us to rigorously study its norm compliance properties. A weak form of norm compliance allows agents to abort execution in order to prevent norm violation. In this paper we investigate a stronger notion of norm compliance that is evaluated over infinite traces. We show that it is not possible for all agents to be strongly compliant with any arbitrary set of norms. We then investigate situations when strong norm compliance can be guaranteed.@en