Arguments and cases: An inevitable intertwining

Skalak, David B.; Rissland, Edwina L.

doi:10.1007/bf00118477

Cited by 137 publications

(88 citation statements)

References 27 publications

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“…At Pittsburgh, Ashley developed CATO, with Aleven (1997), and SMILE and Issue Based Prediction (IBP) with Ashley and Brüninghaus (2009). Meanwhile Rissland continued to develop the HYPO ideas at Amherst producing CABARET with Skalak and Rissland (1992), BankXX with Skalak and M. Timur Friedman Rissland et al (1996) and SPIRE with Rissland and Daniels (1996). A major difference between these two strands was their use and understanding of factors.…”

Section: Discloses Subject To Restrictionmentioning

confidence: 99%

“…Two of the resulting systems are described in papers in this special issue, Skalak and Rissland (1992) and , and the details of these two systems will be left to them. The domains for these systems are the Home Office Deduction (an allowance against income tax when part of one's home is used as an office) for CABARET and personal bankruptcy for BankXX and SPIRE.…”

Section: Beyond Hypomentioning

confidence: 99%

See 1 more Smart Citation

HYPO’S legacy: introduction to the virtual special issue

Bench‐Capon

2017

Artif Intell Law

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Section: Discloses Subject To Restrictionmentioning

confidence: 99%

Section: Beyond Hypomentioning

confidence: 99%

HYPO’S legacy: introduction to the virtual special issue

Bench‐Capon

2017

Artif Intell Law

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“…Hence, a case-based representation of the domain knowledge of the system is more suitable for being applied in dynamic open MAS. From the first uses of argumentation in AI, arguments and cases are intertwined (Skalak and Rissland, 1992). Case-based argumentation particularly reported successful applications in American common law (Bench-Capon and Dunne, 2007).…”

Section: Related Workmentioning

confidence: 99%

Towards real-time agreements

Navarro

Heras

Botti

et al. 2013

Expert Systems with Applications

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In this paper, we deal with the problem of real-time coordination with the more general approach of reaching real-time agreements in MAS. Concretely, this work proposes a real-time argumentation framework in an attempt to provide agents with the ability of engaging in argumentative dialogues and come with a solution for their underlying agreement process within a bounded period of time. The framework has been implemented and evaluated in the domain of a customer support application. Concretely, we consider a society of agents that act on behalf of a group of technicians that must solve problems in a Technology Management Centre (TMC) within a bounded time. This centre controls every process implicated in the provision of technological and customer support services to private or public organisations by means of a call centre. The contract signed between the TCM and the customer establishes penalties if the specified time is exceeded.Keywords: Agreement Technologies, Real-Time, Multi-Agent Systems MotivationMany Multi-Agent Systems (MAS) operate in resource and time-constrained environments. In such domains, scarce resources must be shared between di↵erent agents taking into account that these agents must perform their tasks before a deadline is met. In addition, agents in open MAS are autonomous entities that can have their own knowledge resources, can play di↵erent roles and can have di↵erent objectives and preferences over values that they want to promote with their actions (e.g. an interested agent could want In this paper, we deal with the problem of real-time coordination with the more general approach of reaching real-time agreements in MAS. Therefore, our notion of a real-time agreement may refer to the fair allocation of a scarce resource, but also to the outcome of a negotiation process to make a deal in a sale operation, to the final label assigned in a classification problem, to the final state of the beliefs database of an agent in a beliefs revision problem, and many more. However, any of these processes must be temporal bounded. This is an important aspect to consider in any real-time argumentative process, where a community of agents are able to reach agreements through argumentation before a deadline is met. Any agreement reached after this deadline will be considered of a low quality, or even not valid if we are in a hard real-time environment. Therefore, it is necessary to control every step of the argumentative process in order to predict its duration in time (i.e. we must know the temporal cost of executing each step of the process). Taking into account this prediction, we can guarantee that the agents engaged in the argumentation dialogue will reach an agreement about the outcome of the agreement process (e.g. they will decide the final allocation for a resource, the label of an individual in a classification problem, etc.) before the specified deadline is met. The response provided by the agents does not need to be optimal, since in some cases the best response may require more proce...

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“…Other research works where the computational modelling of arguments has been studied are those on case-based argumentation. From the first uses of argumentation in AI, arguments and cases are intertwined [42]. Case-based argumentation particularly reported successful applications in American common law [7], whose judicial standard orders that similar cases must be resolved with similar verdicts.…”

Section: Computational Requirements For Arguments In Agent Societiesmentioning

confidence: 99%