Moreover, 2 keynote and 2 tutorial papers were invited. Most regular papers were presented in one of these tracks: Smart Contracts, Blockchain, and Rules, Constraint Handling Rules, Event Driven Architectures and Active Database Systems, Legal Rules and Reasoning, Rule-and Ontology-Based Data Access and Transformation, Rule Induction, and Learning. Following up on previous years, RuleML also hosted the 6th RuleML Doctoral Consortium and the 10th International Rule Challenge, which this year was dedicated to applications of rule-based reasoning, such as Rules in Retail, Rules in Tourism, Rules in Transportation, Rules in Geography, Rules in Location-Based Search, Rules in Insurance Regulation, Rules in Medicine, and Rules in Ecosystem Research. The 10th International Rule Challenge Awards went to Ingmar Dasseville, Laurent Janssens, Gerda Janssens, Jan Vanthienen, and Marc Denecker, for their paper Combining DMN and the Knowledge Base Paradigm for Flexible Decision Enactment, and Jacob Feldman for his paper What-If Analyzer for DMN-based Decision Models. As in previous years, RuleML 2016 was also a place for presentations and face-to-face meetings about rule technology standardizations, which this year Mark Your Calendars!

Before engaging in a group venture agents may seek commitments from other members in the group and, based on the level of participation (i.e. the number of actually committed participants), decide whether it is worth joining the venture. Alternatively, agents can delegate this costly process to a (beneficent or non-costly) third-party, who helps seek commitments from the agents. Using methods from Evolutionary Game Theory, this paper shows that, in the context of Public Goods Game, much higher levels of cooperation can be achieved through such centralized commitment management. It provides a more efficient mechanism for dealing with commitment free-riders, those who are not willing to bear the cost of arranging commitments whilst enjoying the benefits provided by the paying commitment proposers. We show that the participation level plays a crucial role in the decision of whether an agreement should be formed; namely, it needs to be more strict in terms of the level of participation required from players of the centralized system for the agreement to be formed; however, once it is done right, it is much more beneficial in terms of the level of cooperation and social welfare achieved. In short, our analysis provides important insights for the design of multi-agent systems that rely on commitments to monitor agents' cooperative behavior.

We know too that guilt may be alleviated by private confession Theorists conceive of shame and guilt as belonging to the (namely to a priest or a psychotherapist) plus the family of self-conscious emotions (Lewis 1990) (Fischer renouncing of past failings in future. Because of their private and Tangney 1995) (Tangney and Dearing 2002), invoked character, such confessions and atonements, given through self-reflection and self-evaluation. Though both their cost (prayers or fees), render temptation defecting less have evolved to promote cooperation, guilt and shame can probable. Public or open confession of guilt can be coordinated be treated separately. Guilt is an inward private phenomenon, with apology for better effect, and the cost appertained though it can promote apology, and even spontaneous to some common good (like charity), or as individual public confession. Shame is inherently public, though it compensation to injured parties.

We report here on our previous research on the evolution of commitment behaviour in the one-off and iterated prisoner's dilemma and relate it to the issue of designing non-human autonomous online systems. We show that it was necessary to introduce an apology/forgiveness mechanism in the iterated case since without this restorative mechanism strategies evolve that take revenge when the agreement fails. As before in online interaction systems, apology and forgiveness seem to provide important mechanisms to repair trust. As such, these result provide, next to the insight into our own moral and ethical considerations, ideas into how (and also why) similar mechanisms can be designed into the repertoire of actions that can be taken by non-human autonomous agents.

Public goods, like food sharing and social health systems, may prosper when prior agreements to contribute are feasible and all participants commit to do so. Yet, free-riders may exploit such agreements, requiring then committers to decide whether to enact the public good when others do not commit. So deciding removes all benefits from free-riders but also from those who are willing to establish the beneficial resource. Here we discuss our work wherein we show, within the framework of the one-shot Public Goods Game (PGG) and using methods of Evolutionary Game Theory (EGT), that (i) implementing extra measures, delimiting benefits to free-riders, often leads to more favorable societal outcomes, especially in larger groups and highly beneficial public goods situations, even if so doing is costlier, and (ii) when restriction mechanism is not available, participation level (i.e. how many other players commit to the PGG cooperation) plays a crucial role in the decision making of commitment proposers, for their survival as well as for promoting the emergence of cooperation. Hence, there exist ethical fine tunings to be observed whenever establishing PGGs, be they for humans or non-humans, for otherwise the supporting joint moral ground may escape from under everyone’s feet.

Update semantics for Answer-Set Programming assign models to sequences of answer-set programs which result from the iterative process of updating programs by programs. Each program in the sequence represents an update of the preceding ones. One of the enduring problems in this context is state condensing, or the problem of determining a single logic program that faithfully represents the sequence of programs. Such logic program should 1) be written in the same alphabet, 2) have the same stable models, and 3) be equivalent to the sequence of programs when subject to further updates. It has been known for more than a decade that update semantics easily lead to non-minimal stable models, so an update sequence cannot be represented by a single non-disjunctive program. On the other hand, more expressive classes of programs were never considered, mainly because it was not clear how they could be updated further. In this paper we solve the state condensing problem for two foundational rule update semantics, using nested logic programs. Furthermore, we also show that disjunctive programs with default negation in the head can be used for the same purpose.

In this paper we take a step towards using Argumentation in Social Networksand introduce Social Abstract Argumentation Frameworks, an extension of Dung'sAbstract Argumentation Frameworks that incorporates social voting.We propose a class of semantics for these new Social Abstract Argumentation Frameworks and prove some important non-trivial properties which are crucialfor their applicability in Social Networks.