4,113 research outputs found
Alert-BDI: BDI Model with Adaptive Alertness through Situational Awareness
In this paper, we address the problems faced by a group of agents that
possess situational awareness, but lack a security mechanism, by the
introduction of a adaptive risk management system. The Belief-Desire-Intention
(BDI) architecture lacks a framework that would facilitate an adaptive risk
management system that uses the situational awareness of the agents. We extend
the BDI architecture with the concept of adaptive alertness. Agents can modify
their level of alertness by monitoring the risks faced by them and by their
peers. Alert-BDI enables the agents to detect and assess the risks faced by
them in an efficient manner, thereby increasing operational efficiency and
resistance against attacks.Comment: 14 pages, 3 figures. Submitted to ICACCI 2013, Mysore, Indi
Applying tropos to socio-technical system design and runtime configuration
Recent trends in Software Engineering have introduced the importance of reconsidering the traditional idea of software design as a socio-tecnical problem, where human agents are integral part of the system along with hardware and software components. Design and runtime support for Socio-Technical Systems (STSs) requires appropriate modeling techniques and
non-traditional infrastructures. Agent-oriented software methodologies are natural solutions to the development of STSs, both humans and technical components are conceptualized and analyzed as part of the same system. In this paper, we illustrate a number of Tropos features that we believe fundamental to support the development and runtime reconfiguration of STSs.
Particularly, we focus on two critical design issues: risk analysis and location variability. We show how they are integrated and used into a planning-based approach to support the designer in evaluating and choosing the best design alternative. Finally, we present a generic framework to develop self-reconfigurable STSs
CAMP-BDI: an approach for multiagent systems robustness through capability-aware agents maintaining plans
Rational agent behaviour is frequently achieved through the use of plans, particularly
within the widely used BDI (Belief-Desire-Intention) model for intelligent agents. As
a consequence, preventing or handling failure of planned activity is a vital component
in building robust multiagent systems; this is especially true in realistic environments,
where unpredictable exogenous change during plan execution may threaten intended
activities.
Although reactive approaches can be employed to respond to activity failure through
replanning or plan-repair, failure may have debilitative effects that act to stymie recovery
and, potentially, hinder subsequent activity. A further factor is that BDI agents typically
employ deterministic world and plan models, as probabilistic planning methods
are typical intractable in realistically complex environments. However, deterministic
operator preconditions may fail to represent world states which increase the risk of
activity failure.
The primary contribution of this thesis is the algorithmic design of the CAMP-BDI
(Capability Aware, Maintaining Plans) approach; a modification of the BDI reasoning
cycle which provides agents with beliefs and introspective reasoning to anticipate
increased risk of failure and pro-actively modify intended plans in response.
We define a capability meta-knowledge model, providing information to identify
and address threats to activity success using precondition modelling and quantitative
quality estimation. This also facilitates semantic-independent communication of capability
information for general advertisement and of dependency information - we define
use of the latter, within a structured messaging approach, to extend local agent algorithms
towards decentralized, distributed robustness. Finally, we define a policy based
approach for dynamic modification of maintenance behaviour, allowing response to
observations made during runtime and with potential to improve re-usability of agents
in alternate environments.
An implementation of CAMP-BDI is compared against an equivalent reactive system
through experimentation in multiple perturbation configurations, using a logistics
domain. Our empirical evaluation indicates CAMP-BDI has significant benefit if activity
failure carries a strong risk of debilitative consequence
An Abstract Formal Basis for Digital Crowds
Crowdsourcing, together with its related approaches, has become very popular
in recent years. All crowdsourcing processes involve the participation of a
digital crowd, a large number of people that access a single Internet platform
or shared service. In this paper we explore the possibility of applying formal
methods, typically used for the verification of software and hardware systems,
in analysing the behaviour of a digital crowd. More precisely, we provide a
formal description language for specifying digital crowds. We represent digital
crowds in which the agents do not directly communicate with each other. We
further show how this specification can provide the basis for sophisticated
formal methods, in particular formal verification.Comment: 32 pages, 4 figure
BDI reasoning with normative considerations
F. Meneguzzi thanks Fundaç ao de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS, Brazil) for the financial support through the ACI program (Grant ref. 3541-2551/12-0) and the ARD program (Grant ref. 12/0808-5), as well as Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) through the Universal Call (Grant ref. 482156/2013-9) and PQ fellowship (Grant ref. 306864/2013-4). N. Oren and W.W. Vasconcelos acknowledge the support of the Engineering and Physical Sciences Research Council (EPSRC, UK) within the research project “Scrutable Autonomous Systems” (SAsSY11, Grant ref. EP/J012084/1).Peer reviewedPostprin
Towards Verifiably Ethical Robot Behaviour
Ensuring that autonomous systems work ethically is both complex and
difficult. However, the idea of having an additional `governor' that assesses
options the system has, and prunes them to select the most ethical choices is
well understood. Recent work has produced such a governor consisting of a
`consequence engine' that assesses the likely future outcomes of actions then
applies a Safety/Ethical logic to select actions. Although this is appealing,
it is impossible to be certain that the most ethical options are actually
taken. In this paper we extend and apply a well-known agent verification
approach to our consequence engine, allowing us to verify the correctness of
its ethical decision-making.Comment: Presented at the 1st International Workshop on AI and Ethics, Sunday
25th January 2015, Hill Country A, Hyatt Regency Austin. Will appear in the
workshop proceedings published by AAA
Agents for educational games and simulations
This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications
An Analysis of the Notion of Need for the Representation of Public Services
Many Public Administrations structure their services around the notion
of users’ need. However, there is a gap between private, subjectively perceived
needs (self-attributed) and needs that are attributed by PA to citizens (heteroattributed).
Because of the gap, citizens’ needs are often only partially satisfied by
PAs services. This gap is in part due to the fact that the meaning of the word “need”
is ambiguous and full of antinomic nuances. The purpose of this paper is to formulate
a definition of “need” suitable for citizens’ needs management with respect to
PA’s services offering, and to provide an accurate ontological analysis of the notion
of “need” and the network of concepts that relate to it
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