4 research outputs found

    Explaining BDI Agent Behaviour Through Dialogue

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    This work arose out of conversations at a Lorentz Workshop on the Dynamics of Multi-Agent Systems (2018). Thanks are due Koen Hindriks and Vincent Koeman for their input. The work was supported by the UKRI/EPSRC RAIN [EP/R026084], SSPEDI [EP/P011829/1 ] and FAIR-SPACE [EP/R026092] Robotics and AI Hubs and the Trustworthy Autonomous Systems Verifiability Node [EP/V026801/1]. Both authors contributed equally to the work, and author names are listed in alphabetical order.Peer reviewedPublisher PD

    A temporal argumentation approach to cooperative planning using dialogues

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    In this article, we study a dialogue-based approach to multi-agent collaborative plan search in the framework of t-DeLP, an extension of DeLP for defeasible temporal reasoning. In t-DeLP programs, temporal facts and rules combine into arguments, which compare against each other to decide which of their conclusions are to prevail. By adding temporal actions for multiple agents to this argumentative logic programming framework, one obtains a centralized planning framework. In this planning system, it can be shown that breadth-first search is sound and complete for both forward and backward planning. The main contribution is to extend these results in centralized planning to cooperative planning tasks, where the executing agents themselves are assumed to have reasoning and planning abilities. In particular, we propose a planning algorithm where agents exchange information on plans using suitable dialogues. We show that the soundness and completeness properties of centralized t-DeLP plan search are preserved, so the dialoguing agents will reach an agreement upon a joint plan if and only if some solution exists.This research was partially supported by the projects Epistemic Protocol Synthesis (FFI2011-15945- E), EdeTRI (TIN2012-39348-C02-01) and AT (CONSOLIDER-INGENIO 2010, CSD2007-00022), funded by the MINECO Spanish Ministry. We would also like to thank the anonymous reviewers for their helpful suggestions.Peer reviewe

    A temporal argumentation approach to cooperative planning using dialogues

    No full text
    In this paper, we study a dialogue-based approach to multi-agent collaborative plan search in the framework of t-DeLP, an extension of DeLP for defeasible temporal reasoning. In t-DeLP programs, temporal facts and defeasible temporal rules combine into arguments, which compare against each other to decide which of their conclusions are to prevail. A backward centralized planning system built on this logical argumentative framework has been already studied in a previous work. In this paper, we consider a distributed collaborative scenario where agents exchange information using suitable dialogues. Agents cooperate to generate arguments and actions (plan steps), and to detect argument threats to plans. We show that the soundness and completeness properties of centralized t-DeLP plan search are preserved. © 2013 Springer-Verlag.The authors thank the reviewers for their helpful comments. They also acknowledge support of the Spanish CONSOLIDER-INGENIO 2010 project Agreement Technologies (CSD2007-00022), the MINECO project EdeTRI (TIN2012-39348-C02-01) and the Generalitat de Catalunya grant 2009-SGR-1434.Peer Reviewe

    An Algorithmic Theory of the Policy Process

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    With a few exceptions, current theories of the policy process do not model or measure the policy process using the graphical process notations that are common within information science, business administration and many natural sciences. The reason is that in the post-war period the needs of business process analysis came to dominate social science applications of process science whilst the needs of public policy process analysis remained largely unaddressed. As a result, modern graphical process notations can encode and quantify the instrumental properties of cost and efficiency of a business process, but not the normative properties of transparency, accountability or legitimacy of the much more complex policy making process. There have been many other unfortunate consequences. Business process modelling evolved into business process reengineering and became a critical enabler of a period of unprecedented hyper-globalization commencing in the 1990’s. However, it did so by encoding and quantifying the instrumental dimensions of cost and efficiency of globalized production processes and not their normative dimensions of domestic employment and social welfare transfers. We live with the consequences to this day of the emergence of destabilizing populist national movements and rising security and defense tensions between former trading partners. However, in recent years, there have been several important new developments. Firstly, a new class of process modelling tools has emerged at the juncture of the disciplines of information science and business administration that can model much more complex governance and policy-making processes as rules based declarative process graphs instead of sequence based imperative process graphs. Secondly, information science is now introducing a capacity for normative reasoning and moral dilemma resolution into a range of technologies from multi-agent systems and artificial societies to self-driving vehicles and autonomous battle drones. This creates new opportunities for a collaboration between policy process analysis and information science to reengineer legacy policy making processes and organizations in terms of normatively driven declarative processes. Not only must these reengineered policy making processes score better against instrumental criteria of cost and efficiency but also against the normative criteria of transparency, accountability, and legitimacy. Consequently, the metrics presented in this dissertation re-connect public policy process analysis with the tools and results of decades of process research in the fields of information science, business administration and many natural sciences, and supports a new theory of the public policy process as an algorithm whose purpose is the generation of solutions to public goods allocation problems. To illustrate the principles of the techniques involved and the utility of the approach, a case study analysis and prediction of Chinese public health policy response to the COVID-19 pandemic of 2020/21 is presented
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