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Adaptive Execution in Complex Dynamic Worlds Robert James Firby Yale University 1989 A robot acting in the real world must use flexible plans because actions will sometimes fail to produce desired effects, and unexpected events will sometimes demand the robot shift its attention. A plan is usually construed as a list of primitive robot actions to be executed one after another but in a complex domain, a plan must be structured to cope effectively with the myriad unpredictable details it will encounter during execution. However, adding structure to a plan involves more than augmenting the primitive plan representation; it requires a complete model of interaction with the world called situation-driven execution. Situation-driven execution assumes that a plan consists of tasks with three major components: a satisfaction test, a window of activity, and a set of execution methods that are appropriate in different circumstances. Execution of such a plan proceeds by selecting an unsatisfied t...

This paper describes the Query Rewrite facility of the Starburst extensible database system, a novel phase of query optimization. We present a suite of rewrite rules used in Starburst to transform queries into equivalent queries for faster execution, and also describe the production rule engine which is used by Starburst to choose and execute these rules. Examples are provided demonstrating that these Query Rewrite transformations lead to query execution time improvements of orders of magnitude, suggesting that Query Rewrite in general --- and these rewrite rules in particular --- are an essential step in query optimization for modern database systems. 1 Introduction In traditional database systems, query optimization typically consists of a single phase of processing in which access methods, join orders and join methods are chosen to provide an efficient plan for executing a user's declarative query. We refer to this phase as plan optimization. In this paper we present a distinct ph...

We present a priority system which is particularly suited for production rules coupled to databases. In this system, there are default priorities between all rules and overriding user-defined priorities between particular rules. Rule processing using this system is repeatable: for a given set of rules and priorities, the rules are considered for execution in the same order if the same set of transactions is executed twice on the same initial database state. The rule order adheres to the default order as closely as possible: rules are considered in the same order as the default order unless user-defined precedence constraints force an inversion. We present data structures and efficient algorithms for implementing such a priority system. We show how the data structures can be incrementally maintained as user-defined priorities are altered. We also discuss how the proposed scheme can be extended to build a multi-level hierarchical priority system. 1 Introduction Incorporation of producti...

Pattern matching is an important operation used in many applications such as functional programming, rewriting and rule-based expert systems. By preprocessing the patterns into a DFA-like automaton, we can rapidly select the matching pattern(s) in a single scan of the relevant portions of the input term. This automaton is typically based on left-to-right traversal of the patterns. By adapting the traversal order to suit the set of input patterns, it is possible to considerably reduce the space and matching time requirements of the automaton.

Rules and frames are two knowledge representation schemes whose strengths and weakness are complementary to each other. Although several previous systems have attempted to integrate the two, few efforts have been made to incorporate the terminological knowledge of the frame-based systems into the rule-based paradigm. To achieve a deep integration of the two schemes, we have developed and implemented a CLASsification-based Production system (CLASP). This paper describes two major processes of CLASP: a semantic pattern matcher and a pattern classifier. The semantic pattern matcher extends the pattern matching capabilities of rule-based systems through the use of terminological knowledge. The pattern classifier enables the system to compute a rule's specificity, which is useful for conflict resolution, based on the semantics of its left hand side. The paradigm not only enhances the reasoning capabilities of rule-based systems, but also helps to reduce the cost of maintaining such systems ...

When rules are executed in a parallel production system, the goal of control is to ensure both that a highquality solution is achieved and that processing resources are used effectively. We argue that the conventional conflict resolution algorithm is not suitable as a control mechanism for parallel rule-firing systems. The necessity for examining all eligible rules within a system imposes a synchronization delay which limits processor utilization. Rather than perform conflict resolution, we propose that rules should be executed asynchronously as soon as they become enabled, however, this approach leaves the problem of controlling the computation unsolved. We have identified three distinct types of control, program sequencing, heuristic control, and dynamic scheduling, which are required for efficient and correct parallel execution of rules. We discuss the issues involved in implementing each type of control without undue overhead within the context of our system, a parallel rule-firin...

An intelligent agent must interact with dynamic entities in real time. Because it cannot predict all events that will occur, it must notice and respond to important unanticipated events. However, insuring execution of the best possible operation at each point in time conflicts with meeting deadlines, especially as event rate and number of known operations increase. The problem is: How can an agent with limited resources execute high-quality operations in constant time, despite increases in event rate and number of known operations? To support this capability in a blackboard architecture, we replace the conventional reasoning cycle with a satisficing cycle. To bound cycle time, it interrupts triggering to execute the best operation available when either it finds a "good enough" operation or a deadline occurs. To insure the availability of high-quality operations when interrupts occur, it uses dynamic control plans to order its consideration of events and known reasoning operations best-...

Abstract—Thirty years after Forgy’s seminal dissertation, Rete remains the de facto standard matching algorithm. Despite promising research results, alternative algorithms such as TREAT and LEAPS have had little impact on modern production rule engines. Constraint Handling Rules (CHR) is a high-level, declarative programming language, similar to production rules. In recent years, CHR has increasingly been used in a wide range of general-purpose applications. State-of-the-art CHR systems use LEAPS-like lazy matching, and implement a large body of novel program analyses and optimization techniques to further improve performance. While obviously related, CHR and production rules research have mostly evolved independently from each other. With this article, we aim to foster cross-fertilization of implementation techniques. We provide a lucid, comprehensive overview of CHR’s rule evaluation methodology, and survey recent contributions to the field of lazy matching. Our empirical evaluation confirms Rete-based engines would surely benefit from incorporating similar techniques and optimizations.

In this chapter we will describe and analyze a simulation of a factual information seeking system for a subsection of the "yellow pages". The subsection contains information about (i) car hire (ii) restaurants, and (iii) personal insurance. The simulation was