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Lin Padgham

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45 papers
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45

JAAMAS Journal 2026 Journal Article

Formalisations of Capabilities for BDI-Agents

  • Lin Padgham
  • Patrick Lambrix

Abstract Intentional agent systems are increasingly being used in a wide range of complex applications. Capabilities has recently been introduced into some of these systems as a software engineering mechanism to support modularity and reusability while still allowing meta-level reasoning. This paper presents possible formalisations of capabilities within the framework of beliefs, goals and intentions and indicates how capabilities can affect agent reasoning about its intentions. We define a style of agent commitment which we refer to as a self-aware agent which allows an agent to modify its goals and intentions as its capabilities change. We also indicate which aspects of the specification of a BDI interpreter are affected by the introduction of capabilities and give some indications of additional reasoning which could be incorporated into an agent system on the basis of both the theoretical analysis and the existing implementation.

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IJCAI Conference 2020 Conference Paper

Optimising Partial-Order Plans Via Action Reinstantiation

  • Max Waters
  • Lin Padgham
  • Sebastian Sardina

This work investigates the problem of optimising a partial-order plan’s (POP) flexibility through the simultaneous transformation of its action ordering and variable binding constraints. While the former has been extensively studied through the notions of deordering and reordering, the latter has received much less attention. We show that a plan’s variable bindings are often related to resource usage and their reinstantiation can yield more flexible plans. To do so, we extend existing POP optimality criteria to support variable reinstantiation, and prove that checking if a plan can be optimised further is NP-complete. We also propose a MaxSAT-based technique for increasing plan flexibility and provide a thorough experimental evaluation that suggests that there are benefits in action reinstantiation.

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AAMAS Conference 2018 Conference Paper

A new Hierarchical Agent Protocol Notation

  • Michael Winikoff
  • Nitin Yadav
  • Lin Padgham

Agent interaction protocols are a key aspect of the design of multiagent systems. However, commonly-used notations are, we argue, difficult to use, and lack expressiveness in certain areas. In this paper we present a new notation for expressing interaction protocols, focussing on key issues that we have found to be problematic. The notation is evaluated against criteria, and using a human subject evaluation of usability.

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ICAPS Conference 2018 Conference Paper

Plan Relaxation via Action Debinding and Deordering

  • Max Waters
  • Bernhard Nebel
  • Lin Padgham
  • Sebastian Sardiña

While seminal work has studied the problem of relaxing the ordering of a plan’s actions, less attention has been given to the problem of relaxing and modifying a plan’s variable bindings. This paper studies the problem of relaxing a plan into a partial plan which specifies which operators must be executed, but need not completely specify their order or variable bindings. While partial plans can provide an agent with additional flexibility and robustness at execution time, many operations over partial plans are intractable. This paper tackles this problem by proposing and empirically evaluating a fixed-parameter tractable algorithm which searches for tractable, flexible partial plans.

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JAAMAS Journal 2017 Journal Article

A new Hierarchical Agent Protocol Notation

  • Michael Winikoff
  • Nitin Yadav
  • Lin Padgham

Abstract Agent interaction descriptions (or protocols) are a key aspect of the design of multi-agent systems. However, in the authors’ extensive experience, the notations commonly used for specification are both difficult to use, and lack expressiveness in certain areas. Some desired modular representations are impossible to express, while others result in specifications that are unwieldy and difficult to follow. In this paper we present a new notation for expressing interaction protocols, focussing on key issues that we have found to be problematic: the ability to define flexible data-driven protocols; representation of roles including their mapping to agents; and hierarchical modularity. We provide the semantics for our notation and illustrate its use with three diverse case studies. Finally we evaluate this notation using objectively assessable criteria that we argue contribute substantially to pragmatic usability, and using a human subject evaluation of the notation’s usability.

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IJCAI Conference 2017 Conference Paper

Emergency Evacuation Simulator (EES) - a Tool for Planning Community Evacuations in Australia

  • Dhirendra Singh
  • Lin Padgham

This work addresses the problem of encoding cognitive agents that are capable of complex reasoning beyond simple rules, within agent-based models (ABM). This is particularly important for social simulation where agents represent people. We provide a general solution to this problem through infrastructure that allows the integration of state-of-the-art Belief-Desire-Intention (BDI) and ABM systems. In this paper, we demonstrate how this infrastructure is being used to help emergency services in Australia plan for community evacuations.

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JAAMAS Journal 2016 Journal Article

Integrating BDI Agents with Agent-Based Simulation Platforms

  • Dhirendra Singh
  • Lin Padgham
  • Brian Logan

Abstract Agent-based models (ABMs) are increasingly being used for exploring and supporting decision making about social science scenarios involving modelling of human agents. However existing agent-based simulation platforms (e. g. , SWARM, Repast) provide limited support for the simulation of more complex cognitive agents required by such scenarios. We present a framework that allows Belief-Desire-Intention (BDI) cognitive agents to be embedded in an ABM system. Architecturally, this means that the “brains” of an agent can be modelled in the BDI system in the usual way, while the “body” exists in the ABM system. The architecture is flexible in that the ABM can still have non-BDI agents in the simulation, and the BDI-side can have agents that do not have a physical counterpart (such as an organisation). The framework addresses a key integration challenge of coupling event-based BDI systems, with time-stepped ABM systems. Our framework is modular and supports integration of off-the-shelf BDI systems with off-the-shelf ABM systems. The framework is Open Source, and all integrations and applications are available for use by the modelling community.

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ECAI Conference 2016 Conference Paper

Summary Information for Reasoning About Hierarchical Plans

  • Lavindra de Silva
  • Sebastian Sardiña
  • Lin Padgham

Hierarchically structured agent plans are important for efficient planning and acting, and they also serve (among other things) to produce "richer" classical plans, composed not just of a sequence of primitive actions, but also "abstract" ones representing the supplied hierarchies. A crucial step for this and other approaches is deriving precondition and effect "summaries" from a given plan hierarchy. This paper provides mechanisms to do this for more pragmatic and conventional hierarchies than in the past. To this end, we formally define the notion of a precondition and an effect for a hierarchical plan; we present data structures and algorithms for automatically deriving this information; and we analyse the properties of the presented algorithms. We conclude the paper by detailing how our algorithms may be used together with a classical planner in order to obtain abstract plans.

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JAAMAS Journal 2015 Journal Article

Improving domain-independent intention selection in BDI systems

  • Max Waters
  • Lin Padgham
  • Sebastian Sardina

Abstract The Belief Desire Intention (BDI) agent paradigm provides a powerful basis for developing complex systems based on autonomous intelligent agents. These agents have, at any point in time, a set of intentions encoding the various tasks the agent is working on. Despite its importance, the problem of selecting which intention to progress at any point in time has received almost no attention and has been mostly left to the programmer to resolve in an application-dependent manner. In this paper, we implement and evaluate two domain-independent intention selection mechanisms based on the ideas of enablement checking and low coverage prioritisation. Through a battery of automatically generated synthetic tests and one real program, we compare these with the commonly used intention selection mechanisms of First-In-First-Out ( FIFO ) and Round Robin ( RR ). We found that enablement checking, which is incorporated into low coverage prioritisation, is never detrimental and provides substantial benefits when running vulnerable programs in dynamic environments. This is a significant finding as such a check can be readily applied to FIFO and RR, giving an extremely simple and effective mechanism to be added to existing BDI frameworks. In turn, low coverage prioritisation provides a significant further benefit.

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ECAI Conference 2014 Conference Paper

Integrating BDI Agents into a MATSim Simulation

  • Lin Padgham
  • Kai Nagel
  • Dhirendra Singh
  • Qingyu Chen

MATSim is a mature and powerful traffic simulator, used for large scale traffic simulations, primarily to assess likely results of various infrastructure or road network changes. More recently there has been work to extend MATSim to allow its use in applications requiring what has been referred to as "within day replanning". In the work described here we have coupled MATSim with a BDI (Belief Desire Intention) system to allow both more extensive modelling of the agent's decision making, as well as reactivity to environmental situations. The approach used allows for all agents to be "intelligent" or for some to be "intelligent"/reactive, while others operate according to plans that are static within a single day. The former is appropriate for simulations such as a bushfire evacuation, where all agents will be reacting to the changing environment. The latter is suited to introducing agents such as taxis into a standard MATSim simulation, as they cannot realistically have a predetermined plan, but must constantly respond to the current situation. We have prototype applications for both bushfire evacuation and taxis. By extending the capabilities of MATSim to allow agents to respond intelligently to changes in the environment, we facilitate the use of MATSim in a wide range of simulation applications. The work also opens the way for MATSim to be used alongside other simulation components, in a simulation integrating multiple components.

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ECAI Conference 2014 Conference Paper

OpenSim: A framework for integrating agent-based models and simulation components

  • Dhirendra Singh
  • Lin Padgham

The growing use of agent-based modelling and simulation for complex systems analysis has led to the availability of numerous published models. However, reuse of existing models in new simulations, for studying new problems, is largely not attempted. This is mainly because there is no systematic way of integrating agent-based models, that deals with the nuances of complex interactions and overlaps in concepts between components, in the shared environment. In this paper we present an open source framework, called OpenSim, that allows such integrated simulations to be built in a modular way, by linking together agent-based and other models. OpenSim is designed to be easy to use, and we give examples of the kinds of simulations we have built with this framework.

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AAMAS Conference 2012 Conference Paper

Goal-Driven Approach To Open-Ended Dialogue Management using BDI Agents

  • Wilson Wong
  • Lawrence Cavedon
  • John Thangarajah
  • Lin Padgham

We describe a BDI (Belief, Desire, Intention) approach and architecture for a conversational virtual companion embodied as a child’s Toy. Our aim is to support both structured conversation-based activities (e. g. , story-telling, collaborative games) as well as more free-flowing, engaging dialogue with variation and some unpredictability. We argue that a goal-oriented approach to the agent’s conversational capabilities provides these competing capabilities.

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AAMAS Conference 2012 Conference Paper

Measuring Plan Coverage and Overlap for Agent Reasoning

  • John Thangarajah
  • Sebastian Sardina
  • Lin Padgham

In Belief Desire Intention (BDI) agent systems it is usual for goals to have a number of plans that are possible ways of achieving the goal, applicable in different situations, usually captured by a \emph{context condition}. In Agent Oriented Software Engineering it has been suggested that a designer should be conscious of whether a goal has \emph{complete coverage}, that is, is there some plan that is applicable for every situation. Similarly a designer should be conscious of \emph{overlap}, that is, for a given goal, are there situations where more than one plan could be applicable for achieving that goal. In this paper we further develop these notions in two ways, and then describe how they can be used both in agent reasoning and agent system development. Firstly, we replace the boolean value for basic coverage and overlap with numerical measures, and explain how these may be calculated. Secondly, we describe a measure that combines these basic measures, with the characteristics of the coverage/overlap in the goal-plan tree below a given goal. We then describe how these domain independent mesures can be used for both plan selection and intention selection, as well as for guidance in agent system design and development.

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AAMAS Conference 2012 Conference Paper

Revising Conflicting Intention Sets in BDI Agents

  • Steven Shapiro
  • Sebastian Sardina
  • John Thangarajah
  • Lawrence Cavedon
  • Lin Padgham

Autonomous agents typically have several goals they are pursuing simultaneously. Even if the goals themselves are not necessarily inconsistent, choices made about how to pursue each of these goals may well result in a set of intentions which are conflicting. A rational autonomous agent should be able to reason about and modify its set of intentions to take account of such issues. This paper presents the semantics of some preferences regarding modified sets of intentions. We look at the possibility of simply deleting some intention(s) but more importantly we also look at the possibility of modifying intentions, such that the goals will still be achieved but in a different way.

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IJCAI Conference 2011 Conference Paper

Integrating Learning into a BDI Agent for Environments with Changing Dynamics

  • Dhirendra Singh
  • Sebastian Sardina
  • Lin Padgham
  • Geoff James

We propose a framework that adds learning for improving plan selection in the popular BDI agent programming paradigm. In contrast with previous proposals, the approach given here is able to scale up well with the complexity of the agent's plan library. Technically, we develop a novel confidence measure which allows the agent to adjust its reliance on the learning dynamically, facilitating in principle infinitely many (re)learning phases. We demonstrate the benefits of the approach in an example controller for energy management.

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AAMAS Conference 2011 Conference Paper

Scenarios for System Requirements Traceability and Testing

  • John Thangarajah
  • Gaya Jayatilleke
  • Lin Padgham

Scenarios in current design methodologies, provide a natural way for the users to identify the inputs and outputs of the system revolving around a particular interaction process. A scenario typically consists of a sequence of steps which captures a particular run of the system and satisfies some aspect of the requirements. In this work we add additional structure to the scenarios used in the Prometheus agent development methodology. This additional structure then facilitates both traceability and automated testing. We describe our process for mapping the scenarios and their steps to the initial detailed design, where we then maintain the traceability as the design develops. The structured action lists that we define for both scenarios and their variations provides the basis for facilitating automated testing of system behavior. We describe how we use the newly defined structure within the scenarios to facilitate testing, describing how we automate test case generation, execution and analysis.

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JAAMAS Journal 2010 Journal Article

A BDI agent programming language with failure handling, declarative goals, and planning

  • Sebastian Sardina
  • Lin Padgham

Abstract Agents are an important technology that have the potential to take over contemporary methods for analysing, designing, and implementing complex software. The Belief-Desire-Intention (BDI) agent paradigm has proven to be one of the major approaches to intelligent agent systems, both in academia and in industry. Typical BDI agent-oriented programming languages rely on user-provided “plan libraries” to achieve goals, and online context sensitive subgoal selection and expansion. These allow for the development of systems that are extremely flexible and responsive to the environment, and as a result, well suited for complex applications with (soft) real-time reasoning and control requirements. Nonetheless, complex decision making that goes beyond, but is compatible with, run-time context-dependent plan selection is one of the most natural and important next steps within this technology. In this paper we develop a typical BDI-style agent-oriented programming language that enhances usual BDI programming style with three distinguished features: declarative goals, look-ahead planning, and failure handling. First, an account that mixes both procedural and declarative aspects of goals is necessary in order to reason about important properties of goals and to decouple plans from what these plans are meant to achieve. Second, lookahead deliberation about the effects of one choice of expansion over another is clearly desirable or even mandatory in many circumstances so as to guarantee goal achievability and to avoid undesired situations. Finally, a failure handling mechanism, suitably integrated with both declarative goals and planning, is required in order to model an adequate level of commitment to goals, as well as to be consistent with most real BDI implemented systems.

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AAMAS Conference 2010 Conference Paper

An Architecture for Modular Distributed Simulation with Agent-Based Models

  • David Scerri
  • Sarah Hickmott
  • Alexis Drogoul
  • Lin Padgham

Agent-based simulations are an increasingly popular meansof exploring and understanding complex social systems. Inorder to be useful, these simulations must capture a range ofaspects of the modeled situation, each possibly requiring distinct expertise. Moreover, different paradigms may be usefulin modelling, ranging from those that use many lightweightreactive agents, to those that use cognitive agents, to thosethat focus on agent teams and organisational structures. There is need for an architecture which supports the development of a large simulation, through the integrationof separately developed modules. This paper describes aframework and architecture which facilitates the integrationof multiple agent-based simulations into a single globalsimulation. This architecture naturally supports distributedsimulation and incremental development, which are waysof addressing the computational and conceptual complexityof such systems. In this paper we focus particularly onhow to ensure proper management of simulation data thatis affected by agents in different modules, at the samelogical time. We also provide some preliminary performanceevaluation addressing scalability, as well as a comparison ofhow other available systems handle the issue of shared data.

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AAMAS Conference 2010 Conference Paper

Bushfire BLOCKS: A Modular Agent-Based Simulation

  • David Scerri
  • Sarah Hickmott
  • Fabio Zambetta
  • Ferdinand Gouw
  • Isaac Yehuda
  • Lin Padgham

Bushfire BLOCKS is a modular, distributed, agent-basedsimulation for exploring and informing bushfire responsestrategies. Separate independent modules capture the firespread, evacuation of traffic and human behaviour such asthe decision whether to remain at property. These moduleshave been developed largely independently, using paradigmsand data models appropriate to their individual purpose. Modules are integrated into a single global simulationvia central services for managing time advancement andaccess to shared variables. Execution is distributed, withmodules running on different machines, whilst a custominterface enables viewing and control from one screen. Theunderlying architecture of this system facilitates extensionof individual modules and addition of new modules, withlimited alteration to other modules.

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AAMAS Conference 2010 Conference Paper

Eclipse-based Prometheus Design Tool

  • Hongyuan Sun
  • John Thangarajah
  • Lin Padgham

The Prometheus Design Tool (PDT) is a graphical tool that is used to design a Multi-Agent System following the Prometheus Methodology. This paper describes the latest version of PDT which is now integrated into the Eclipse platform, enabling the users to accomplish the full development life-cycle of an agent-oriented application in one IDE and also inherit the rich set of product development features that Eclipse provides. This version of PDT also aims to support simpler integration with tools from other AOSE methodologies where appropriate.

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AAMAS Conference 2010 Conference Paper

Learning Context Conditions for BDI Plan Selection

  • Dhirendra Singh
  • Sebastian Sardina
  • Lin Padgham
  • Stephane Airiau

An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element oflearning from experience. In particular, the so-called context conditions of plans, on which the whole model relies for plan selection, are restricted to be boolean formulas that are to be specified atdesign/implementation time. To address these limitations, we propose a novel BDI programming framework that, by suitably modeling context conditions as decision trees, allows agents to learn theprobability of success for plans based on previous execution experiences. By using a probabilistic plan selection function, the agentscan balance exploration and exploitation of their plans. We developand empirically investigate two extreme approaches to learning thenew context conditions and show that both can be advantageousin certain situations. Finally, we propose a generalization of theprobabilistic plan selection function that yields a middle-groundbetween the two extreme approaches, and which we thus argue isthe most flexible and simple approach.

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AAMAS Conference 2009 Conference Paper

First Principles Planning in BDI Systems

  • Lavindra de Silva
  • Sebastian Sardina
  • Lin Padgham

BDI (Belief, Desire, Intention) agent systems are very powerful, but they lack the ability to incorporate planning. There has been some previous work to incorporate planning within such systems. However, this has either focussed on producing low-level plan sequences, losing much of the domain knowledge inherent in BDI systems, or has been limited to HTN (Hierarchical Task Network) planning, which cannot find plans other than those specified by the programmer. In this work, we incorporate classical planning into a BDI agent, but in a way that respects and makes use of the procedural domain knowledge available, by producing abstract plans that can be executed using such knowledge. In doing so, we recognize an intrinsic tension between striving for abstract plans and, at the same time, ensuring that unnecessary actions, unrelated to the specific goal to be achieved, are avoided. We explore this tension, by first characterizing the set of “ideal” abstract plans that are non-redundant while maximally abstract, and then developing a more limited but feasible account in which an abstract plan is “specialized” into a new abstract plan that is non-redundant and preserves abstraction as much as possible. We describe an algorithm to compute such a plan specialization, as well as algorithms for the production of a valid high level plan, by deriving abstract planning operators from the BDI program.

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AAMAS Conference 2008 Conference Paper

Automated Unit Testing Intelligent Agents in PDT

  • Zhiyong Zhang
  • John Thangarajah
  • Lin Padgham

The Prometheus Design Tool (PDT) is an agent development tool that supports the Prometheus design methodology and includes features like automated code generation. We enhance this tool by adding a feature that allows the automated unit testing of agents that are built from within PDT.

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AAMAS Conference 2007 Conference Paper

AUML Protocols and Code Generation in the Prometheus Design Tool

  • Lin Padgham
  • John Thangarajah
  • Michael Winikoff

Prometheus is an agent-oriented software engineering methodology. The Prometheus Design Tool (PDT) is a software tool that supports a designer who is using the Prometheus methodology. PDT has recently been extended with two significant new features: support for Agent UML interaction protocols, and code generation.

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AAMAS Conference 2007 Conference Paper

Goals in the Context of BDI Plan Failure and Planning

  • Sebastian Sardina
  • Lin Padgham

We develop a Belief-Desire-Intention (BDI) style agent-oriented programming language with special emphasis on the semantics of goals in the presence of the typical BDI failure handling present in many BDI systems and a novel account of hierarchical lookahead planning. The work builds incrementally on two existing languages and accommodates three type of goals: classical BDI-style event goals, declarative goals, and planning goals. We mainly focus on the dynamics of these type of goals and, in particular, on a kind of commitment scheme that brings the new language closer to the solid existing work in agent theory. To that end, we develop a semantics that recognises the usual hierarchical structure of active goals as well as their declarative aspects. In contrast with previous languages, the new language prevents an agent from blindly persisting with a (blocked) subsidiary goal when an alternative strategy for achieving a higher-level motivating goal exists. In addition, the new semantics ensures watchfulness by the agent to ensure that goals that succeed or are deemed impossible are immediately dropped, thus conforming to the requirements of basic rational commitment strategy. Finally, a mechanism for the proactive adoption of new goals, other than the mere reaction to events, and a formal account of interaction with the external environment are provided. We believe that the new language is an important step towards turning practical BDI programming languages more compatible with the established results in the area of agent theory.

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AAMAS Conference 2007 Conference Paper

Searching for Joint Gains in Automated Negotiations Based on Multi-criteria Decision Making Theory

  • Quoc Bao Vo
  • Lin Padgham

It is well established by conflict theorists and others that successful negotiation should incorporate "creating value" as well as "claiming value. " Joint improvements that bring benefits to all parties can be realised by (i) identifying attributes that are not of direct conflict between the parties, (ii) tradeoffs on attributes that are valued differently by different parties, and (iii) searching for values within attributes that could bring more gains to one party while not incurring too much loss on the other party. In this paper we propose an approach for maximising joint gains in automated negotiations by formulating the negotiation problem as a multi-criteria decision making problem and taking advantage of several optimisation techniques introduced by operations researchers and conflict theorists. We use a mediator to protect the negotiating parties from unnecessary disclosure of information to their opponent, while also allowing an objective calculation of maximum joint gains. We separate out attributes that take a finite set of values ( simple attributes ) from those with continuous values, and we show that for simple attributes, the mediator can determine the Pareto-optimal values. In addition we show that if none of the simple attributes strongly dominates the other simple attributes, then truth telling is an equilibrium strategy for negotiators during the optimisation of simple attributes. We also describe an approach for improving joint gains on non-simple attributes, by moving the parties in a series of steps, towards the Pareto-optimal frontier.

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IJCAI Conference 2003 Conference Paper

Detecting & Avoiding Interference Between Goals in Intelligent Agents

  • John Thangarajah
  • Lin Padgham
  • Michael Winikoff

Pro-active agents typically have multiple simultaneous goals. These may interact with each other both positively and negatively. In this paper we provide a mechanism allowing agents to detect and avoid a particular kind of negative interaction where the effects of one goal undo conditions that must be protected for successful pursuit of another goal. In order to detect such interactions we maintain summary information about the definite and potential conditional requirements and resulting effects of goals and their associated plans. We use these summaries to guard protected conditions by scheduling the execution of goals and plan steps. The algorithms and data structures developed allow agents to act rationally instead of blindly pursuing goals that will conflict.

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AAAI Conference 2000 Conference Paper

Agent Capabilities: Extending BDI Theory

  • Lin Padgham

Intentional agent systems are increasingly being used in a wide range of complex applications. Capabilities has recently been introduced into one of these systems as a software engineering mechanism to support modularity and reusability while still allowing meta-level reasoning. This paper presents a formalisation of capabilities within the framework of beliefs, goals and intentions and indicates how capabilities can affect agent reasoning about its intentions. We define a style of agent commitment which we refer to as a self-aware agent which allows an agent to modify its goals and intentions as its capabilities change. We also indicate which aspects of the specification of a BDI interpreter are affected by the introduction of capabilities and give some indications of additional reasoning which could be incorporated into an agent system on the basis of both the theoretical analysis and the existing implementation.

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IJCAI Conference 1993 Conference Paper

A Terminological Logic with Defaults: A Definition and an Application

  • Lin Padgham
  • Tingting Zhang

In this paper we present a terminological language which includes defaults, and a definition of default subsumption based on the notion of skeptical in­ heritance in default reasoning. Except for the in­ clusion of defaults the language is limited when compared to most terminological logics. However defaults are a necessary construct in many applica­ tions and we suggest that the language presented here is a useful tradeoff between different types of expressivity We present an algorithm for classify­ ing new concepts into the default hierarchy repre­ senting the taxonomy, and in addition an algorithm for what we call default classification, suitable for interactive reasoning about individuals. We de­ scribe a diagnosis application which has been im­ plemented using this language and reasoning mech­ anisms. We present an evaluation of the diagnosis application on the basis of comparison with 63 pa­ tient protocols. We conclude that the language pre­ sented is in fact adequate for the application pre­ sented here and hypothesize that it i. s interesting for a significant group of applications.

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