Adjustable Deliberation for Self-Managing Systems: Supporting Situated Autonomic Computing Prof. A. Taleb-Bendiab School of Computing Liverpool John Moores.

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Adjustable Deliberation for Self-Managing Systems: Supporting Situated Autonomic Computing Prof. A. Taleb-Bendiab School of Computing Liverpool John Moores University

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 2 Scope Background Background Engineering Autonomy: Engineering Autonomy: The Story So far The Story So far Our motivation Our motivation Deliberative Framework Deliberative Framework Modelling Deliberative systems Modelling Deliberative systems Case Study and example Case Study and example Conclusions & future work Conclusions & future work Q&A Q&A

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 3 Autonomy: The Story So Far! Coping with complexity and dependability concerns via Coping with complexity and dependability concerns via Management by delegation: devolving software management, maintenance and many other functions to the software itself Management by delegation: devolving software management, maintenance and many other functions to the software itself Self-organising, self-healing, sentient, Self-organising, self-healing, sentient, self-adaptive, self-aware, etc. self-adaptive, self-aware, etc. Progress towards realizing such software has mainly been informed by a number of guiding approaches; Progress towards realizing such software has mainly been informed by a number of guiding approaches; Bio vs eco-inspired models Bio vs eco-inspired models control systems theory, dynamic planning systems control systems theory, dynamic planning systems Logic and decision theoretic approaches Logic and decision theoretic approaches Reflection for self-aware systems Reflection for self-aware systems Policy-based Policy-based

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 4 Engineering Autonomy #1 Currently design models of the 1 st generation ”autonomic systems” employ; Currently design models of the 1 st generation ”autonomic systems” employ; Explicit managed autonomy via policies and rule sets predefining at design-time all extraneous behaviour using constructs such as; Explicit managed autonomy via policies and rule sets predefining at design-time all extraneous behaviour using constructs such as; Event Condition Action, Design by contract Event Condition Action, Design by contract Separation of concerns – AOP, etc. Separation of concerns – AOP, etc. Yes, these are well tested design principles, but for they are limiting and not scalable – see lifetime management. Yes, these are well tested design principles, but for they are limiting and not scalable – see lifetime management. unfeasible to model and thus predict every conceivable event or state that may arise unfeasible to model and thus predict every conceivable event or state that may arise Evolving policies and control model Evolving policies and control model Autonomy is not accessible – regulated or adjustable Autonomy is not accessible – regulated or adjustable

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 5 Engineering Autonomy #2 Problem Statement: Problem Statement: How do we access and/or adjustable deliberative autonomy? How do we access and/or adjustable deliberative autonomy? How do we specify it and reason on it? How do we specify it and reason on it? How do we dynamically modify it and enact it? How do we dynamically modify it and enact it?

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 6 A Cybernetic Approach: The Viable System Model Beer’s VSM implements a control & communication structure via hierarchies of homeostats (feedback loops) Beer’s VSM implements a control & communication structure via hierarchies of homeostats (feedback loops) 6 major systems ensure ‘viability’ of the system 6 major systems ensure ‘viability’ of the system ImplementationS1 ImplementationS1 MonitoringS2 MonitoringS2 AuditS3* AuditS3* ControlS3 ControlS3 Intelligence S4 Intelligence S4 Normative S5 Normative S5 Offers an extensible, recursive, model-based architecture, devolving autonomy to sub-systems Offers an extensible, recursive, model-based architecture, devolving autonomy to sub-systems Autonomic Systems Anticipatory Self-awareness Deliberative

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 7 A Viable Intelligent Agent Architecture

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 8 An Adjustable Deliberation Deliberative frameworks: Deliberative frameworks: Beliefs-Desires-Intentions (BDI) Bratman et al. Beliefs-Desires-Intentions (BDI) Bratman et al. Beliefs: representing the current state of its world Beliefs: representing the current state of its world desires representing the agent’s ideal world. desires representing the agent’s ideal world. Mismatch, between B & D triggers the intentions to rectify the current state to the ideal state. Mismatch, between B & D triggers the intentions to rectify the current state to the ideal state. To include normative behaviour and thus cooperation and coordination in multi-agent systems To include normative behaviour and thus cooperation and coordination in multi-agent systems Belief-Obligation-Intention-Desire model (BOID) Belief-Obligation-Intention-Desire model (BOID) Epistemic-Deontic-Axiologic (EDA) model Epistemic-Deontic-Axiologic (EDA) model Extended BDI Extended BDI

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 9 Modelling Autonomy Via Situation Calculus SC was conceived as a tool model states or situations as objects to be reasoned about with FOL (McCarthy, 1963). SC was conceived as a tool model states or situations as objects to be reasoned about with FOL (McCarthy, 1963). SC used to formalizes the behaviour of dynamically changing systems. SC used to formalizes the behaviour of dynamically changing systems. Support concurrent actions and timing constraints. Support concurrent actions and timing constraints. Each situation can be viewed as a history of previous actions. Each situation can be viewed as a history of previous actions. Action, guards and time can be modelled at deliberation points in an autonomic setting. Action, guards and time can be modelled at deliberation points in an autonomic setting.

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 10 Enacting Adjustable Autonomic Models #1 How do we use SC formulation and deploy it? How do we use SC formulation and deploy it? Many approaches including Many approaches including Handcrafted code, automated code gen., etc. Handcrafted code, automated code gen., etc. We are developing a declarative meta- language –JBel based on C# We are developing a declarative meta- language –JBel based on C# Developed a Concept-Aided-Situation- Prediction-Action (CA-SPA) construct Developed a Concept-Aided-Situation- Prediction-Action (CA-SPA) construct

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 11 Enacting Adjustable Autonomic Models #2

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 12

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 13 A Case Study #1

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 14 Grid-Based Decision Support Grid-based decision support systems Grid-based decision support systems Combining evidence and guidelines Combining evidence and guidelines Clinical pathway development studio Clinical pathway development studio Demo. for Demo. for Breast cancer Breast cancer OOH – Dental triage service OOH – Dental triage service BASAN BASAN

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 15 So What?

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 16 Conclusions and Further works Adjustable/bounded Autonomy is an attractive idea Adjustable/bounded Autonomy is an attractive idea So far positive evaluation So far positive evaluation with “small’ish” examples with “small’ish” examples Further to go to model, enhance and evaluate Programming, interaction and/or control models. Complexity Scale, diversity and Uncertainty Organisation including; Designed systems vs self-organising system, ownership Governance including; Reactive vs proactive behavioural models Trust issues Evaluation and Analysis Metrics Acknowledgement EPSRC Christies and Linda McCartney NHS trusts

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 17 That’s the end – so I’m off !

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 18 Extra

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 19 Clouds: Self-Regenerative Model

Input: 1.Conceptual models Output: 1.Aspects Models 2.Task-model 3.Service model Stakeholders Concerns Definition Input: 1.Service models 2.JReference patterns Output: 1.S1, S2, S3 and definition 2.Architectural model VSM-Compliant Systems Definition SSM-Centric Tasks Input: Architectural model Interaction/Delegation model Output 1.S*, S4, S5 definition 2.Architectural model 3.Self-governance model Self-governance Definition VSM-Centric Tasks Spiral Model Self-Managing Systems Input: Architectural model Output 1.S1 to S5 enactment 2.Testing properties, etc. 3.Iteration Systems Model Enactment

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 21 So What? -- Dental Triage Demo. Current System Re-engineering New

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 22

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 23

Prof. A. Taleb-Bendiab, Workshop: IEEE ECBS -- Engineering of Autonomic Systems Ease’05, Date: 12/04/2015, Slide: 24 SAC Scenario: E-Fire Services