In this paper, we present the agent programming language POGTGolog (Partially Observable Game-Theoretic Golog), which integrates explicit agent programming in Golog with game-theoretic multi-agent planning in partiall...
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In this paper, we present the agent programming language POGTGolog (Partially Observable Game-Theoretic Golog), which integrates explicit agent programming in Golog with game-theoretic multi-agent planning in partially observable stochastic games. In this framework, we assume one team of cooperative agents acting under partial observability, where the agents may also have different initial belief states and not necessarily the same rewards. POGTGolog allows for specifying a partial control program in a high-level logical language, which is then completed by an interpreter in an optimal way. To this end, we define a formal semantics of POGTGolog programs in terms of Nash equilibria, and we then specify a POGTGolog interpreter that computes one of these Nash equilibria. (C) 2020 Elsevier Inc. All rights reserved.
It is claimed that, in the nascent 'Cognitive Era', intelligent systems will be trained using machine learning techniques rather than programmed by software developers. A contrary point of view argues that mac...
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ISBN:
(纸本)9781450383073
It is claimed that, in the nascent 'Cognitive Era', intelligent systems will be trained using machine learning techniques rather than programmed by software developers. A contrary point of view argues that machine learning has limitations, and, taken in isolation, cannot form the basis of autonomous systems capable of intelligent behaviour in complex environments. In this paper, we argue that the unique strengths of Belief-Desire-Intention (BDI) agent programming languages provide an ideal framework for integrating the wide range of AI capabilities necessary for progress towards the next-generation of intelligent systems.
A multitude of agent-oriented software engineering frameworks exist, most of which are developed by the academic multi-agent systems community. However, these frameworks often impose programming paradigms on their use...
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ISBN:
(纸本)9783030514174;9783030514167
A multitude of agent-oriented software engineering frameworks exist, most of which are developed by the academic multi-agent systems community. However, these frameworks often impose programming paradigms on their users that are challenging to learn for engineers who are used to modern high-level programming languages such as JavaScript and Python. To show how the adoption of agent-oriented programming by the software engineering mainstream can be facilitated, we provide a lean JavaScript library prototype for implementing reasoning-loop agents. The library focuses on core agent programming concepts and refrains from imposing further restrictions on the programming approach. To illustrate its usefulness, we show how the library can be applied to multi-agent systems simulations on the web, deployed to cloud-hosted function-as-a-service environments, and embedded in Python-based data science tools.
In this paper we propose to rethink the development of intelligent agents based on cognitive architectures as a developmental learning process, inspired by theories of learning in children and cognitive development. T...
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ISBN:
(纸本)9781450392136
In this paper we propose to rethink the development of intelligent agents based on cognitive architectures as a developmental learning process, inspired by theories of learning in children and cognitive development. The idea is targeted to explore architectures, methods and tools to systematically develop intelligent agents capable of integrating both practical knowledge and skills designed by developers and knowledge and skills acquired by interacting in properly designed learning environments.
While several BDI logics have been proposed in the area of agent programming, it is not clear how these logics are connected to the agent programs they are supposed to specify. More yet, the reasoning problems in thes...
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ISBN:
(纸本)9781538680230
While several BDI logics have been proposed in the area of agent programming, it is not clear how these logics are connected to the agent programs they are supposed to specify. More yet, the reasoning problems in these logics, being based on modal logic, are not tractable in general, limiting their usage to tackle real-world problems. In this work, we use of Dynamic Preference Logic to provide a semantic foundation to BDI agent programming languages and investigate tractable expressive fragments of this logic to reason about agent programs. With that, we aim to provide a way of implementing semantically grounded agent programming languages with tractable reasoning cycles.
In this work, we investigate the use of Dynamic Preference Logic to encode BDI mental attitudes. Further, exploring this codification and the representation of preferences over possible worlds by preferences over prop...
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ISBN:
(纸本)9781538624074
In this work, we investigate the use of Dynamic Preference Logic to encode BDI mental attitudes. Further, exploring this codification and the representation of preferences over possible worlds by preferences over propositional formulas, here called priority graphs, we comment on how to interpret BDI agent programs in this logic. Also, using the connection between dynamic operations defined over preference models and their encoding as transformations on priority graphs, we show how our logic can be used not only to reason about agent programs, but as a tool to specify reasoning mechanisms to guarantee certain properties in the theory of rationality for the programming language.
We conceptualize a decentralized software application as one constituted from autonomous agents that communicate via asynchronous messaging. Modern software paradigms such as microservices and settings such as the Int...
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We conceptualize a decentralized software application as one constituted from autonomous agents that communicate via asynchronous messaging. Modern software paradigms such as microservices and settings such as the Internet of Things evidence a growing interest in decentralized applications. Constructing a decentralized application involves designing agents as independent local computations that coordinate successfully to realize the application's requirements. Moreover, a decentralized application is susceptible to faults manifested as message loss, delay, and reordering. We contribute Mandrake, a programming model for decentralized applications that tackles these challenges without relying on infrastructure guarantees. Specifically, we adopt the construct of an information protocol that specifies messaging between agents purely in causal terms and can be correctly enacted by agents in a shared-nothing environment over nothing more than unreliable, unordered transport. Mandrake facilitates (1) implementing protocol-compliant agents by introducing a programming model;(2) transforming protocols into fault-tolerant ones with simple annotations;and (3) a declarative policy language that makes it easy to implement fault-tolerance in agents based on the capabilities in protocols. Mandrake's significance lies in demonstrating a straightforward approach for constructing decentralized applications without relying on coordination mechanisms in the infrastructure, thus achieving some of the goals of the founders of networked computing from the 1970s.
The Autonomy and Verification group(1) sits within the Department of Computer Science(2) at the University of Manchester. The group has a long history of research into agents and multi-agent systems (both at Mancheste...
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The Autonomy and Verification group(1) sits within the Department of Computer Science(2) at the University of Manchester. The group has a long history of research into agents and multi-agent systems (both at Manchester and, previously, at the University of Liverpool) particularly in the areas of formal specification and verification, multi-agent programming, ethical agent reasoning, and swarms, teams and organisations.
We demonstrate Orpheus, a novel programming model for engineering BDI agents that communicate on the basis of protocols. In Orpheus, protocols are specified in BSPL and agents are implemented in Jason. Given a protoco...
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ISBN:
(纸本)9798400714269
We demonstrate Orpheus, a novel programming model for engineering BDI agents that communicate on the basis of protocols. In Orpheus, protocols are specified in BSPL and agents are implemented in Jason. Given a protocol, Orpheus tooling generates a Jason adapter that exposes a simple interface for sending messages based on protocol state. Orpheus shines in the implementation of flexible, loosely-coupled agents, long a challenge for BDI-based agent programming approaches.
To apply BDI agents to real-world scenarios, the reality-gap, between the low-level data (perceptions) and their high-level representation (beliefs), must be bridged. This is usually achieved by a manual mapping. Ther...
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ISBN:
(数字)9783030974572
ISBN:
(纸本)9783030974572;9783030974565
To apply BDI agents to real-world scenarios, the reality-gap, between the low-level data (perceptions) and their high-level representation (beliefs), must be bridged. This is usually achieved by a manual mapping. There are two problems with this solution: (i) if the environment changes, the mapping has to be changed as well (by the developer);(ii) part of the mapping might end up being implemented at the agent level increasing the code complexity and reducing its generality. In this paper, we present a general approach to automate the mapping between low-level data and high-level beliefs through the use of transducers. These transducers gather information from the environment and map them to high-level beliefs according to formal temporal specifications. We present our technique and we show its applicability through a case study involving the remote inspection of a nuclear plant.
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