Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Cashmore, Michael"'
In this work we consider a new interpretation of fairness in decision making problems. Building upon existing fairness formulations, we focus on how to reason over fairness from a temporal perspective, taking into account the fairness of a history of
Externí odkaz:
http://arxiv.org/abs/2408.13208
Autor:
Acero, Fernando, Zehtabi, Parisa, Marchesotti, Nicolas, Cashmore, Michael, Magazzeni, Daniele, Veloso, Manuela
Portfolio optimization involves determining the optimal allocation of portfolio assets in order to maximize a given investment objective. Traditionally, some form of mean-variance optimization is used with the aim of maximizing returns while minimizi
Externí odkaz:
http://arxiv.org/abs/2403.16667
Industries frequently adjust their facilities network by opening new branches in promising areas and closing branches in areas where they expect low profits. In this paper, we examine a particular class of facility location problems. Our objective is
Externí odkaz:
http://arxiv.org/abs/2403.09925
Autor:
Mana, Kyle, Acero, Fernando, Mak, Stephen, Zehtabi, Parisa, Cashmore, Michael, Magazzeni, Daniele, Veloso, Manuela
Discrete optimization belongs to the set of $\mathcal{NP}$-hard problems, spanning fields such as mixed-integer programming and combinatorial optimization. A current standard approach to solving convex discrete optimization problems is the use of cut
Externí odkaz:
http://arxiv.org/abs/2307.08816
Autor:
Krarup, Benjamin, Krivic, Senka, Magazzeni, Daniele, Long, Derek, Cashmore, Michael, Smith, David E.
In automated planning, the need for explanations arises when there is a mismatch between a proposed plan and the user's expectation. We frame Explainable AI Planning in the context of the plan negotiation problem, in which a succession of hypothetica
Externí odkaz:
http://arxiv.org/abs/2103.15575
In order to ensure the robust actuation of a plan, execution must be adaptable to unexpected situations in the world and to exogenous events. This is critical in domains in which committing to a wrong ordering of actions can cause the plan failure, e
Externí odkaz:
http://arxiv.org/abs/2003.09401
One of the major limitations for the employment of model-based planning and scheduling in practical applications is the need of costly re-planning when an incongruence between the observed reality and the formal model is encountered during execution.
Externí odkaz:
http://arxiv.org/abs/1911.07318
Autor:
Cashmore, Michael, Collins, Anna, Krarup, Benjamin, Krivic, Senka, Magazzeni, Daniele, Smith, David
Explainable AI is an important area of research within which Explainable Planning is an emerging topic. In this paper, we argue that Explainable Planning can be designed as a service -- that is, as a wrapper around an existing planning system that ut
Externí odkaz:
http://arxiv.org/abs/1908.05059
In order to engender trust in AI, humans must understand what an AI system is trying to achieve, and why. To overcome this problem, the underlying AI process must produce justifications and explanations that are both transparent and comprehensible to
Externí odkaz:
http://arxiv.org/abs/1810.06338
Autor:
Cashmore, Michael
This work explores the idea of classical Planning as Quantified Boolean Formulae. Planning as Satisfiability (SAT) is a popular approach to Planning and has been explored in detail producing many compact and efficient encodings, Planning-specific sol
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.588963