2,997 research outputs found
Probabilistic Hybrid Action Models for Predicting Concurrent Percept-driven Robot Behavior
This article develops Probabilistic Hybrid Action Models (PHAMs), a realistic
causal model for predicting the behavior generated by modern percept-driven
robot plans. PHAMs represent aspects of robot behavior that cannot be
represented by most action models used in AI planning: the temporal structure
of continuous control processes, their non-deterministic effects, several modes
of their interferences, and the achievement of triggering conditions in
closed-loop robot plans.
The main contributions of this article are: (1) PHAMs, a model of concurrent
percept-driven behavior, its formalization, and proofs that the model generates
probably, qualitatively accurate predictions; and (2) a resource-efficient
inference method for PHAMs based on sampling projections from probabilistic
action models and state descriptions. We show how PHAMs can be applied to
planning the course of action of an autonomous robot office courier based on
analytical and experimental results
Norm Monitoring under Partial Action Observability
In the context of using norms for controlling multi-agent systems, a vitally
important question that has not yet been addressed in the literature is the
development of mechanisms for monitoring norm compliance under partial action
observability. This paper proposes the reconstruction of unobserved actions to
tackle this problem. In particular, we formalise the problem of reconstructing
unobserved actions, and propose an information model and algorithms for
monitoring norms under partial action observability using two different
processes for reconstructing unobserved actions. Our evaluation shows that
reconstructing unobserved actions increases significantly the number of norm
violations and fulfilments detected.Comment: Accepted at the IEEE Transaction on Cybernetic
Genetic algorithm design of neural network and fuzzy logic controllers
Genetic algorithm design of neural network and fuzzy logic controller
Transforming specifications of observable behaviour into programs
A methodology for deriving programs from specifications of observable
behaviour is described. The class of processes to which this methodology
is applicable includes those whose state changes are fully definable by labelled
transition systems, for example communicating processes without
internal state changes. A logic program representation of such labelled
transition systems is proposed, interpreters based on path searching techniques
are defined, and the use of partial evaluation techniques to derive
the executable programs is described
The DAB model of drawing processes
The problem of automatic drawing was investigated in two ways. First, a DAB model of drawing processes was introduced. DAB stands for three types of knowledge hypothesized to support drawing abilities, namely, Drawing Knowledge, Assimilated Knowledge, and Base Knowledge. Speculation concerning the content and character of each of these subsystems of the drawing process is introduced and the overall adequacy of the model is evaluated. Second, eight experts were each asked to understand six engineering drawings and to think aloud while doing so. It is anticipated that a concurrent protocol analysis of these interviews can be carried out in the future. Meanwhile, a general description of the videotape database is provided. In conclusion, the DAB model was praised as a worthwhile first step toward solution of a difficult problem, but was considered by and large inadequate to the challenge of automatic drawing. Suggestions for improvements on the model were made
A parallel expert system for the control of a robotic air vehicle
Expert systems can be used to govern the intelligent control of vehicles, for example the Robotic Air Vehicle (RAV). Due to the nature of the RAV system the associated expert system needs to perform in a demanding real-time environment. The use of a parallel processing capability to support the associated expert system's computational requirement is critical in this application. Thus, algorithms for parallel real-time expert systems must be designed, analyzed, and synthesized. The design process incorporates a consideration of the rule-set/face-set size along with representation issues. These issues are looked at in reference to information movement and various inference mechanisms. Also examined is the process involved with transporting the RAV expert system functions from the TI Explorer, where they are implemented in the Automated Reasoning Tool (ART), to the iPSC Hypercube, where the system is synthesized using Concurrent Common LISP (CCLISP). The transformation process for the ART to CCLISP conversion is described. The performance characteristics of the parallel implementation of these expert systems on the iPSC Hypercube are compared to the TI Explorer implementation
Faster Mutation Analysis via Equivalence Modulo States
Mutation analysis has many applications, such as asserting the quality of
test suites and localizing faults. One important bottleneck of mutation
analysis is scalability. The latest work explores the possibility of reducing
the redundant execution via split-stream execution. However, split-stream
execution is only able to remove redundant execution before the first mutated
statement.
In this paper we try to also reduce some of the redundant execution after the
execution of the first mutated statement. We observe that, although many
mutated statements are not equivalent, the execution result of those mutated
statements may still be equivalent to the result of the original statement. In
other words, the statements are equivalent modulo the current state.
In this paper we propose a fast mutation analysis approach, AccMut. AccMut
automatically detects the equivalence modulo states among a statement and its
mutations, then groups the statements into equivalence classes modulo states,
and uses only one process to represent each class. In this way, we can
significantly reduce the number of split processes. Our experiments show that
our approach can further accelerate mutation analysis on top of split-stream
execution with a speedup of 2.56x on average.Comment: Submitted to conferenc
A Distributed Calculus for Role-Based Access Control
Role-based access control (RBAC) is increasingly attracting attention because it reduces the complexity and cost of security administration by interposing the notion of role in the assignment of permissions to users. In this paper, we present a formal framework relying on an extension of the Ļ calculus to study the behavior of concurrent systems in a RBAC scenario. We define a type system ensuring that the specified policy is respected during computations, and a bisimulation to equate systems. The theory is then applied to three meaningful examples, namely finding the āminimalā policy to run a given system, refining a system to be run under a given policy (whenever possible), and minimizing the number of users in a given system without changing the overall behavior
- ā¦