What is the Expressive Power of Disjunctive Preconditions?

While there seems to be a general consensus about the expressive power of a number of language features in planning formalisms, one can nd many dierent statements about the expressive power of disjunctive preconditions. Using the "compilability framework," we show that preconditions in conjunctive normal form add to the expressive power of propositional strips, which con rms a conjecture by Bäckström. Furthe

What is the expressive power of disjunctive preconditions?

While there seems to be a general consensus about the expressive power of a number of language features in planning formalisms, once can find many different statements about the expressive power of disjunctive preconditions. Using the 'compilability framework', we show that preconditions in conjunctive normal form add to the expressive power of propositional STRIPS, which confirms a conjecture by Baeckstroem. Further, we show that preconditions in conjunctive normal form do not add any expressive power once we have conditional effects. (orig.)SIGLEAvailable from TIB Hannover: RR 5165(118) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Planning in BDI agent systems

 Belief-Desire-Intention (BDI) agent systems are a popular approach to developing agents for complex and dynamic environments. These agents rely on context sensitive expansion of plans, acting as they go, and consequently, they do not incorporate a generic mechanism to do any kind of “look-ahead” or offline planning. This is useful when, for instance, important resources may be consumed by executing steps that are not necessary for a goal; steps are not reversible and may lead to situations in which a goal cannot be solved; and side effects of steps are undesirable if they are not useful for a goal. In this thesis, we incorporate planning techniques into BDI systems. First, we provide a general mechanism for performing “look-ahead” planning, using Hierarchical Task Network (HTN) planning techniques, so that an agent may guide its selection of plans for the purpose of avoiding negative interactions between them. Unlike past work on adding such planning into BDI agents, which do so only at the implementation level without any precise semantics, we provide a solid theoretical basis for such planning. Second, we incorporate first principles planning into BDI systems, so that new plans may be created for achieving goals. Unlike past work, which focuses on creating low-level plans, losing much of the domain knowledge encoded in BDI agents, we introduce a novel technique where plans are created by respecting and reusing the procedural domain knowledge encoded in such agents; our abstract plans can be executed in the standard BDI engine using this knowledge. Furthermore, we recognise 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. To explore this tension, we characterise the set of “ideal” abstract plans that are non-redundant while maximally abstract, and then develop a more limited but feasible account where an abstract plan is “specialised” into a plan that is non-redundant and as abstract as possible. We present theoretical properties of the planning frameworks, as well as insights into their practical utility

Kennzahlenbasierte Steuerung, Koordination und Aktionsplanung in Multiagentensystemen

To be of practical use, the implementation of flexible and modular agent-based cyber-physical systems (CPS) for real-world autonomous control applications in Industry 4.0 oftentimes requires the domain-specific software agents to adhere to the organization's overall qualitative and quantitative business goals, usually expressed in terms of numeric key performance indicators (KPI). In this thesis, a general software framework for multi-agent systems (MAS) and CPS is developed that facilitates the integration and configuration of KPI-related objectives into the agents' individual decision processes. It allows the user of an agent system to define new KPIs and associated multi-criteria goals and supports inter-agent coordination as well as detailed KPI-based action planning, all at runtime of the MAS. The domain-independent components of the proposed KPI framework are implemented as a Java programming library and evaluated in a simulated production planning and control scenario