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James Harland

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24 papers
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24

TCS Journal 2022 Journal Article

Generating candidate busy beaver machines (or how to build the zany zoo)

  • James Harland

The busy beaver problem is a well-known example of a non-computable function. In order to determine a particular value of this function, it is necessary to generate and classify a large number of Turing machines. The advent of cloud computing provides unparallelled opportunities to explore this problem, but also to develop infrastructures that support distributed investigations and relevant computational evidence for all results obtained, such as a list of all machines of a given size together with their classifications. This list can then be used for variants of the problem or related ones such as the placid platypus problem. We investigate how to generate classes of machines to be considered for the busy beaver problem, which involves separating the generation of machines from their analysis. We discuss the relationship between quadruple and quintuple variants of Turing machines, and show that the latter are more general than the former. We give some formal results to justify our strategy for minimising the number of machines generated, and define a process reflecting this strategy for generating machines. We describe our implementation, and the results of generating various classes of machines with up to 5 states or up to 5 symbols, all of which (together with our code) are available on the author's website.

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TCS Journal 2016 Journal Article

Busy beaver machines and the observant otter heuristic (or how to tame dreadful dragons)

  • James Harland

The busy beaver is a well-known specific example of a non-computable function. Whilst many aspects of this problem have been investigated, it is not always easy to find thorough and convincing evidence for the claims made about the maximality of particular machines, and the phenomenal size of some of the numbers involved means that it is not obvious that the problem can be feasibly addressed at all. In this paper we address both of these issues. We discuss a framework in which the busy beaver problem and similar problems may be addressed, and the appropriate processes for providing evidence of claims made. We also show how a simple heuristic, which we call the observant otter, can be used to evaluate machines with an extremely large number of execution steps required to terminate. We also show empirical results for an implementation of this heuristic which show how this heuristic is effective for all known ‘monster’ machines.

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AAMAS Conference 2016 Conference Paper

Requirements Specification in the Prometheus Methodology via Activity Diagrams (JAAMAS Extended Abstract)

  • Yoosef Abushark
  • John Thangarajah
  • Tim Miller
  • Michael Winikoff
  • James Harland

In this work we extend a popular agent design methodology, Prometheus, and improve the understandability and maintainability of requirements by automatically generating UML activity diagrams from existing requirements models; namely scenarios and goal hierarchies. The approach is general to all the methodologies that support similar notions in specifying requirements.

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JAAMAS Journal 2016 Journal Article

Requirements specification via activity diagrams for agent-based systems

  • Yoosef Abushark
  • Tim Miller
  • James Harland

Abstract Goal-oriented agent systems are increasingly popular for developing complex applications that operate in highly dynamic environments. As with any software these systems have to be designed starting with the specification of system requirements. In this paper, we extend a popular agent design methodology, Prometheus, and improve the understandability and maintainability of requirements by automatically generating UML activity diagrams from existing requirements models; namely scenarios and goal hierarchies. This approach aims to overcome some of the ambiguity present in the current requirements specification in Prometheus and provide more structure for representing variations. Even though our approach is grounded in Prometheus, it can be generalised to all the methodologies that support similar notions in specifying requirements (i. e. notions of goals and scenarios). We present our approach and an evaluation based on user experiments. The evaluation showed that the activity diagram based approach enhances people’s understanding of the requirements, makes it easier to modify requirements, and easier to check them against the detailed design of the agents for coverage.

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ECAI Conference 2016 Conference Paper

Towards a BDI Player Model for Interactive Narratives

  • Jessica Rivera-Villicana
  • Fabio Zambetta
  • James Harland
  • Marsha Berry

Player Modelling is one of the challenges in Interactive Narratives (INs), where a precise representation of the players mental state is needed to provide a personalised experience. However, how to represent the interaction of the player with the game to make the appropriate decision in the story is still an open question. In this paper, we aim to bridge this gap identifying the information needed to capture the players interaction with an IN using the Belief-Desire-Intention (BDI) model of agency. We present a BDI design to mimic a players interaction with a simplified version of the interactive fiction Anchorhead.

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JAAMAS Journal 2015 Journal Article

Aborting, suspending, and resuming goals and plans in BDI agents

  • James Harland
  • David N. Morley
  • Neil Yorke-Smith

Abstract Intelligent agents designed to work in complex, dynamic environments such as e-commerce must respond robustly and flexibly to environmental and circumstantial changes, including the actions of other agents. An agent must have the capability to deliberate about appropriate courses of action, which may include reprioritising tasks—whether goals or associated plans—aborting or suspending tasks, or scheduling tasks in a particular order. In this article we study mechanisms to enable principled suspend, resuming, and aborting of goals and plans within a Belief-Desire-Intention (BDI) agent architecture. We give a formal and combined operational semantics for these actions in an abstract agent language ( CAN ), thus providing a general mechanism that can be incorporated into several BDI-based agent platforms. The abilities enabled by our semantics provides an agent designer greater flexibility to direct agent operation, offering a generic means to manage the status of goals. We demonstrate the reasoning abilities enabled on a document workflow scenario.

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ECAI Conference 2014 Conference Paper

Checking The Correctness of Agent Designs Against Model-Based Requirements

  • Yoosef B. Abushark
  • Michael Winikoff
  • Tim Miller 0001
  • James Harland
  • John Thangarajah

Agent systems are used for a wide range of applications, and techniques to detect and avoid defects in such systems are valuable. In particular, it is desirable to detect issues as early as possible in the software development lifecycle. We describe a technique for checking the plan structures of a BDI agent design against the requirements models, specified in terms of scenarios and goals. This approach is applicable at design time, not requiring source code. A lightweight evaluation demonstrates that a range of defects can be found using this technique.

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ECAI Conference 2014 Conference Paper

Quantifying the Completeness of Goals in BDI Agent Systems

  • John Thangarajah
  • James Harland
  • David N. Morley
  • Neil Yorke-Smith

Given the current set of intentions an autonomous agent may have, intention selection is the agent's decision which intention it should focus on next. Often, in the presence of conflicts, the agent has to choose between multiple intentions. One factor that may play a role in this deliberation is the level of completeness of the intentions. To that end, this paper provides pragmatic but principled mechanisms for quantifying the level of completeness of goals in a BDI-style agent. Our approach leverages previous work on resource and effects summarization but we go beyond by accommodating both dynamic resource summaries and goal effects, while also allowing a non-binary quantification of goal completeness. We demonstrate the computational approach on an autonomous robot case study.

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JAAMAS Journal 2013 Journal Article

An operational semantics for the goal life-cycle in BDI agents

  • James Harland
  • David N. Morley
  • Neil Yorke-Smith

Abstract A fundamental feature of intelligent agents is their ability to deliberate over their goals. Operating in an environment that may change in unpredictable ways, an agent needs to regularly evaluate whether its current set of goals is the most appropriate set to pursue. The management of goals is thus a key aspect of an agent’s architecture. Focusing on BDI agents, we consider the various types of goals studied in the literature, including both achievement and maintenance goals. We develop a detailed description of goal states (such as whether goals have been suspended or not), and a comprehensive suite of operations that may be applied to goals (including dropping, aborting, suspending and resuming them). We provide an operational semantics corresponding to this detailed description in an abstract agent language ( CAN ), and demonstrate on a detailed real-life scenario. The three key contributions of our generic framework for goal states and transitions are (1) to encompass both goals of accomplishment and rich goals of monitoring, (2) to provide the first specification of abort and suspend for all the common goal types, and (3) to account for plan execution as well as the dynamics of subgoaling. Our semantics clarifies how an agent can manage its goals, based on the decisions that it chooses to make, and further provides a foundation for correctness verification of agent behaviour.

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AAMAS Conference 2011 Conference Paper

Reasoning About Preferences in BDI Agent Systems

  • Simeon Visser
  • John Thangarajah
  • James Harland

BDI agents often have to make decisions about which plan is used to achieve a goal, and in which order goals are to be achieved. In this paper we describe how to incorporate preferences (based on the LPP language) into the BDI execution model.

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IJCAI Conference 2011 Conference Paper

Reasoning about Preferences in Intelligent Agent Systems

  • Simeon Visser
  • John Thangarajah
  • James Harland

Agent systems based on the BDI paradigm need to make decisions about which plans are used to achieve their goals. Usually the choice of which plans to use to achieve a particular goal is left up to the system to determine. In this paper we show how preferences, which can be set by the user of the system, can be incorporated into the BDI execution process and used to guide the choices made.

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AAMAS Conference 2008 Conference Paper

Suspending and Resuming Tasks in Intelligent Agents

  • John Thangarajah
  • James Harland
  • David Morley
  • Neil Yorke-Smith

Intelligent agents designed to work in complex, dynamic environments must respond robustly and flexibly to environmental and circumstantial changes. An agent must be capable of deliberating about appropriate courses of action, which may include reprioritising goals, aborting particular tasks, or scheduling tasks in a particular order. This paper investigates the incorporation of a mechanism to suspend and reconsider tasks within a BDI-style architecture. Such an ability provides an agent designer greater flexibility to direct agent operation, and it offers a generic means for handling conflicts between tasks. We investigate conditions under which a goal or a plan may be suspended, the process for suspending it, and the appropriate behaviours upon resumption. We give an operational semantics for suspending tasks in terms of the abstract agent language CAN, thus providing a general mechanism that can be incorporated into any BDI-based agent programming language.

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AAMAS Conference 2007 Conference Paper

Aborting Tasks in BDI Agents

  • John Thangarajah
  • James Harland
  • David Morley
  • Neil Yorke-Smith

Intelligent agents that are intended to work in dynamic environments must be able to gracefully handle unsuccessful tasks and plans. In addition, such agents should be able to make rational decisions about an appropriate course of action, which may include aborting a task or plan, either as a result of the agent's own deliberations, or potentially at the request of another agent. In this paper we investigate the incorporation of aborts into a BDI-style architecture. We discuss some conditions under which aborting a task or plan is appropriate, and how to determine the consequences of such a decision. We augment each plan with an optional abort-method, analogous to the failure method found in some agent programming languages. We provide an operational semantics for the execution cycle in the presence of aborts in the abstract agent language CAN, which enables us to specify a BDI-based execution model without limiting our attention to a particular agent system (such as JACK, Jadex, Jason, or SPARK). A key technical challenge we address is the presence of parallel execution threads and of sub-tasks, which require the agent to ensure that the abort methods for each plan are carried out in an appropriate sequence.

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AAMAS Conference 2007 Conference Paper

Temporal Linear Logic as a Basis for Flexible Agent Interactions

  • Duc Q. Pham
  • James Harland

Interactions between agents in an open system such as the Internet require a significant degree of flexibility. A crucial aspect of the development of such methods is the notion of commitments, which provides a mechanism for coordinating interactive behaviors among agents. In this paper, we investigate an approach to model commitments with tight integration with protocol actions. This means that there is no need to have an explicit mapping from protocols actions to operations on commitments and an external mechanism to process and enforce commitments. We show how agents can reason about commitments and protocol actions to achieve the end results of protocols using a reasoning system based on temporal linear logic, which incorporates both temporal and resource-sensitive reasoning. We also discuss the application of this framework to scenarios such as online commerce.

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KR Conference 2004 Conference Paper

Observation Expectation Reasoning in Agent Systems

  • Margaret Hamilton
  • James Harland
  • Binh Tran

The computational grounding problem — the gap between the mental models of an agent and its computational model — is a well known problem within the agent research community. For years, it has been believed that obscure ontological status is the principal cause. This acute problem hampers the speed of agent oriented development. In this work, we propose an alternative way for modelling intelligent agents through the concepts of observation and expectation to avoid this problem.

LPAR Conference 1992 Conference Paper

On Resolution in Fragments of Classical Linear Logic

  • James Harland
  • David J. Pym

Abstract We present a proof-theoretic foundation for logic programming in Girard's linear logic. We exploit the permutability properties of two-sided linear sequent calculus to identify appropriate notions of uniform proof, definite formula, goal formula, clause and resolution proof for fragments of linear logic. The analysis of this paper extends earlier work by the present authors to include $negative occurrences of ✠ (par) and positive occurrences of! (of course!) and? (why not?). These connectives introduce considerable difficulty. We consider briefly some of the issues related to the mechanical implementation of our resolution proofs.

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