Mind the gaps: Assuring the safety of autonomous systems from an engineering, ethical, and legal perspective
This paper brings together a multi-disciplinary perspective from systems engineering, ethics, and law to articulate a common language in which to reason about the multi-faceted problem of assuring the safety of autonomous systems. The ...
Recursively modeling other agents for decision making: A research perspective
Individuals exhibit theory of mind, attributing beliefs, intent, and mental states to others as explanations of observed actions. Dennett's intentional stance offers an analogous abstraction for computational agents seeking to ...
Clause vivification by unit propagation in CDCL SAT solvers
Original and learnt clauses in Conflict-Driven Clause Learning (CDCL) SAT solvers often contain redundant literals. This may have a negative impact on solver performance, because redundant literals may deteriorate both the ...
New models for generating hard random boolean formulas and disjunctive logic programs
We propose two models of random quantified boolean formulas and their natural random disjunctive logic program counterparts. The models extend the standard models of random k-CNF formulas and the Chen-Interian model of random 2QBFs. ...
Preference elicitation and robust winner determination for single- and multi-winner social choice
The use of voting schemes based on rankings of alternatives to solve social choice problems can often impose significant burden on voters, both in terms of communication and cognitive requirements. In this paper, we develop techniques ...
Train-O-Matic: Supervised Word Sense Disambiguation with no (manual) effort
Word Sense Disambiguation (WSD) is the task of associating the correct meaning with a word in a given context. WSD provides explicit semantic information that is beneficial to several downstream applications, such as question answering,...
Design and results of the Second International Competition on Computational Models of Argumentation
Argumentation is a major topic in the study of Artificial Intelligence. Since the first edition in 2015, advancements in solving (abstract) argumentation frameworks are assessed in competition events, similar to other closely related ...
Governing convergence of Max-sum on DCOPs through damping and splitting
Max-sum is a version of Belief Propagation, used for solving DCOPs. In tree-structured problems, Max-sum converges to the optimal solution in linear time. Unfortunately, when the constraint graph representing the problem includes ...
Landmark-based approaches for goal recognition as planning
Recognizing goals and plans from complete or partial observations can be efficiently achieved through automated planning techniques. In many applications, it is important to recognize goals and plans not only accurately, but also ...