147,607 research outputs found
Human-aligned artificial intelligence is a multiobjective problem
As the capabilities of artificial intelligence (AI) systems improve, it becomes important to constrain their actions to ensure their behaviour remains beneficial to humanity. A variety of ethical, legal and safety-based frameworks have been proposed as a basis for designing these constraints. Despite their variations, these frameworks share the common characteristic that decision-making must consider multiple potentially conflicting factors. We demonstrate that these alignment frameworks can be represented as utility functions, but that the widely used Maximum Expected Utility (MEU) paradigm provides insufficient support for such multiobjective decision-making. We show that a Multiobjective Maximum Expected Utility paradigm based on the combination of vector utilities and non-linear action–selection can overcome many of the issues which limit MEU’s effectiveness in implementing aligned AI. We examine existing approaches to multiobjective AI, and identify how these can contribute to the development of human-aligned intelligent agents. © 2017, Springer Science+Business Media B.V
Engineering Agent Systems for Decision Support
This paper discusses how agent technology can be applied to the design of advanced Information Systems for Decision Support. In particular, it describes the different steps and models that are necessary to engineer Decision Support Systems based on a multiagent architecture. The approach is illustrated by a case study in the traffic management domain
Supporting decision making process with "Ideal" software agents: what do business executives want?
According to Simon’s (1977) decision making theory, intelligence is the first and most important phase in the decision making process. With the escalation of information resources available to business executives, it is becoming imperative to explore the potential and challenges of using agent-based systems to support the intelligence phase of decision-making. This research examines UK executives’ perceptions of using agent-based support systems and the criteria for design and development of their “ideal” intelligent software agents. The study adopted an inductive approach using focus groups to generate a preliminary set of design criteria of “ideal” agents. It then followed a deductive approach using semi-structured interviews to validate and enhance the criteria. This qualitative research has generated unique insights into executives’ perceptions of the design and use of agent-based support systems. The systematic content analysis of qualitative data led to the proposal and validation of design criteria at three levels. The findings revealed the most desirable criteria for agent based support systems from the end users’ point view. The design criteria can be used not only to guide intelligent agent system design but also system evaluation
An agent-based approach to assess drivers’ interaction with pre-trip information systems.
This article reports on the practical use of a multi-agent microsimulation framework to address the issue of assessing drivers’
responses to pretrip information systems. The population of drivers is represented as a community of autonomous agents,
and travel demand results from the decision-making deliberation performed by each individual of the population as regards
route and departure time. A simple simulation scenario was devised, where pretrip information was made available to users
on an individual basis so that its effects at the aggregate level could be observed. The simulation results show that the
overall performance of the system is very likely affected by exogenous information, and these results are ascribed to demand
formation and network topology. The expressiveness offered by cognitive approaches based on predicate logics, such as the
one used in this research, appears to be a promising approximation to fostering more complex behavior modelling, allowing
us to represent many of the mental aspects involved in the deliberation process
Recommended from our members
A normative approach to multi-agent systems for intelligent buildings
Building Management Systems (BMS) are widely adopted in modern buildings around the world in order to
provide high-quality building services, and reduce the running cost of the building. However, most BMS are
functionality-oriented and do not consider user personalization. The aim of this research is to capture and
represent building management rules using organizational semiotics methods. We implement Semantic
Analysis, which determines semantic units in building management and their relationship patterns of
behaviour, and Norm Analysis, which extracts and specifies the norms that establish how and when these
management actions occur. Finally, we propose a multi-agent framework for norm based building
management. This framework contributes to the design domain of intelligent building management system
by defining a set of behaviour patterns, and the norms that govern the real-time behaviour in a building
Agent Technology in Supply Chains and Networks: An exploration of high potential future applications
This paper reports on an ongoing research project that\ud
is aimed at evaluating how software agents can improve\ud
performance of supply chains and networks. To conduct\ud
this evaluation, first a framework is developed to classify\ud
potential applications of software agents to supply\ud
networks. The framework was used in workshop sessions\ud
with logistics and information systems experts from\ud
industry, software/consultancy and academia to identify\ud
promising areas for agents. Based on the framework and\ud
the outcome of the workshop sessions, this paper presents\ud
promising application areas for the near future and\ud
beyond
- …