HTN-Like Solutions for Classical Planning Problems: An Application to BDI Agent Systems

In this paper we explore the question of what characterises a desirable plan of action and how such a plan could be computed, in the context of systems that already possess a certain amount of hierarchical domain knowledge. In contrast to past work in this setting, which focuses on generating low-level plans, losing much of the domain knowledge inherent in such systems, we argue that plans ought to be HTN-like or abstract, i.e., re-use and respect the user-supplied know-how in the underlying domain. In doing so, we recognise an intrinsic tension between striving for abstract plans but ensuring that unnecessary actions, not linked to the specific goal to be achieved, are avoided. We explore this tension by characterising the set of “ideal” abstract plans that are non-redundant but maximally abstract, and then develop a more limited yet feasible account in which a given (arbitrary) abstract plan is “specialised” into one such non-redundant plan that is as abstract as possible. We present an algorithm that can compute such specialisations, and analyse the theoretical properties of our proposal

An operational semantics for a fragment of PRS

The Procedural Reasoning System (PRS) is arguably the first implementation of the Belief–Desire–Intention (BDI) approach to agent programming. PRS remains extremely influential, directly or indirectly inspiring the development of subsequent BDI agent programming languages. However, perhaps surprisingly given its centrality in the BDI paradigm, PRS lacks a formal operational semantics, making it difficult to determine its expressive power relative to other agent programming languages. This paper takes a first step towards closing this gap, by giving a formal semantics for a significant fragment of PRS. We prove key properties of the semantics relating to PRS-specific programming constructs, and show that even the fragment of PRS we consider is strictly more expressive than the plan constructs found in typical BDI languages

HyperTensioN and Total-order Forward Decomposition optimizations

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Process plan controllers for non-deterministic manufacturing systems

Determining the most appropriate means of producing a given product, i.e., which manufacturing and assembly tasks need to be performed in which order and how, is termed process planning In process planning, abstract manufacturing tasks in a process recipe are matched to available manufacturing resources, e.g., CNC machines and robots, to give an executable process plan. A process plan controller then delegates each operation in the plan to specific manufacturing resources. In this paper we present an approach to the automated computation of process plans and process plan controllers. We extend previous work to support both non-deterministic (i.e., partially controllable) resources, and to allow operations to be performed in parallel on the same part. We show how implicit fairness assumptions can be captured in this setting, and how this impacts the definition of process plans

Digital Manufacturing on a Shoestring - Low-Cost Digital Solutions for Manufacturing SMEs: A Catalogue of Digital Solution Areas

The aim of this paper is to present a catalogue comprising a set of digital solution areas associated with operational challenges that are relevant to a majority of manufacturing small to medium sized enterprises (SMEs). The working catalogue has been developed in consultation with over 100 manufacturing SMEs. The working catalogue describes 59 solution areas identified to the end of 2020. Out of all participants in the study, 86% ranked one of the top 5 items in the catalogue as a key priority for their business. These findings can help increase accessibility to digitalisation for manufacturing SMEs.This work was supported by the Engineering and Physical Sciences Research Council [grant number EPSRC: EP/R032777/1

Realisability of production recipes

There is a rising demand for customised products with a high degree of complexity. To meet these demands, manufacturing lines are increasingly becoming autonomous, networked, and intelligent, with production lines being virtualised into a manufacturing cloud, and advertised either internally to a company, or externally in a public cloud. In this paper, we present a novel approach to two key problems in such future manufacturing systems: the realisability problem (whether a product can be manufactured by a set of manufacturing resources) and the control problem (how a particular product should be manufactured). We show how both production recipes specifying the steps necessary to manufacture a particular product, and manufacturing resources and their topology can be formalised as labelled transition systems, and define a novel simulation relation which captures what it means for a recipe to be realisable on a production topology. We show how a controller that can orchestrate the resources in order to manufacture the product on the topology can be extracted from the simulation relation, and give an algorithm to compute a simulation relation and a controller

A multi-agent framework for capability-based reconfiguration of industrial assembly systems

Rapidly changing market requirements and shorter product lifecycles demand assembly systems that are able to cope with frequently changing resources, resource capabilities and product specifications. This paper presents a multi-agent framework that can adapt an assembly system in order to cope with such changes. The focus of this work is on the ability to plug resources (such as PLCs) into and out of the system, and dynamically aggregate resource capabilities to form more complex ones as resources are plugged in. In addition, an implementation of the framework on an industrial assembly system is discussed, and some insights are provided into some of the key features that product specification languages ought to have to be useful in real world assembly systems, and into the added value of using the proposed framework