A Domain-Independent Algorithm for Plan Adaptation

The paradigms of transformational planning, case-based planning, and plan debugging all involve a process known as plan adaptation - modifying or repairing an old plan so it solves a new problem. In this paper we provide a domain-independent algorithm for plan adaptation, demonstrate that it is sound, complete, and systematic, and compare it to other adaptation algorithms in the literature. Our approach is based on a view of planning as searching a graph of partial plans. Generative planning starts at the graph's root and moves from node to node using plan-refinement operators. In planning by adaptation, a library plan - an arbitrary node in the plan graph - is the starting point for the search, and the plan-adaptation algorithm can apply both the same refinement operators available to a generative planner and can also retract constraints and steps from the plan. Our algorithm's completeness ensures that the adaptation algorithm will eventually search the entire graph and its systematicity ensures that it will do so without redundantly searching any parts of the graph.Comment: See http://www.jair.org/ for any accompanying file

Qualitative and Quantitative Solution Diversity in Heuristic-Search and Case-Based Planning

Planning is a branch of Artificial Intelligence (AI) concerned with projecting courses of actions for executing tasks and reaching goals. AI Planning helps increase the autonomy of artificially intelligent agents and decrease the cognitive load burdening human planners working in challenging domains, such as the Mars exploration projects. Approaches to AI planning include first-principles heuristic search planning and case-based planning. The former conducts a heuristic-guided search in the solution space, while the latter generates new solutions by adapting solutions to previously-solved problems.The ability to generate not just one solution, but a set of meaningfully diverse solutions to each planning problem helps cater to a wider variety of user preferences and needs (which it may be difficult or even unfeasible to acquire and/or represent in their entirety), produce viable alternative courses of action to fall back on in case of failure, counter varied threats in intrusion detection, render computer games more compelling, and provide representative samples of the vast search spaces of planning problems.This work describes a general framework for generating diverse sets of solutions (i.e. courses of action) to planning problems. The general diversity-aware planning algorithm consists of iteratively generating solutions using a composite candidate-solution evaluation criterion taking into account both how promising the candidate solutions appear in their own right and on how likely they are to increase the overall diversity of the final set of solutions. This estimate of diversity is based on distance metrics, i.e. measures of the dissimilarity between two solutions. Distance metrics can be quantitative or qualitative.Quantitative distance measures are domain-independent. They require minimum knowledge engineering, but may not reflect dissimilarities that are truly meaningful. Qualitative distance metrics are domain-specific and reflect, based on the domain knowledge encoded within them, the kind of meaningful dissimilarities that might be identified by a person familiar with the domain.Based on the general framework for diversity-aware planning, three domain-independent planning algorithms have been implemented and are described and evaluated herein. DivFF is a diverse heuristic search planner for deterministic planning domains (i.e. domains for which the assumption is made that any action can only have one possible outcome). DivCBP is a diverse case-based planner, also for deterministic planning domains. DivNDP is a heuristic search planner for nondeterministic planning domains (i.e. domains the descriptions of which include actions with multiple possible outcomes). The experimental evaluation of the three algorithms is conducted on a computer game domain, chosen for its challenging characteristics, which include nondeterminism and dynamism. The generated courses of action are run in the game in order to ascertain whether they affect the game environment in diverse ways. This constitutes the test of their genuine diversity, which cannot be evaluated accurately based solely on their low-level structure.It is shown that all proposed planning systems successfully generate sets of diverse solutions using varied criteria for assessing solution dissimilarity. Qualitatively-diverse solution sets are demonstrated to constantly produce more diverse effects in the game environment than quantitatively-diverse solution sets.A comparison between the two planning systems for deterministic domains, DivCBP and DivFF, reveals the former to be more successful at consistently generating diverse sets of solutions. The reasons for this are investigated, thus contributing to the literature of comparative studies of first-principles and case-based planning approaches. Finally, an application of diversity in planning is showcased: simulating personality-trait variation in computer game characters. Sets of diverse solutions to both deterministic and nondeterministic planning problems are shown to successfully create diverse character behavior in the evaluation environment

The model-based construction of a case-oriented expert system

Second generation expert systems should be based upon an expert\u27s high level understanding of the application domain and upon specific real world experiences. By having an expert categorize different types of relevant experiences and their components, hierarchies of abstract problems and operator classes are determined on the basis of the expert\u27s accumulated problem solving experiences. The expert\u27s global understanding of the domain is integrated with the experiences by a model of expertise. This model postulates problem classes at different levels of abstractions and associated skeletal plans. During a consultation with the expert system previously unseen types of input may be used to delineate a new problem. The application of the expert system can thus be situated in changing environments and contexts. With increasing dissimilarity between the cases that were analyzed during knowledge acquisition and the specific problem that is processed at the time of the application of the system, its performance gracefully degrades by supplying a more and more abstract skeletal plan. More specifically, the search space which is represented by the skeletal plan increases until the competence of the system is exceeded. This paper describes how such a case-oriented expert system is developed for production planning in mechanical engineering

A Prospect for Evolutionary Adequacy: Merge and the Evolution and Development of Human Language

Biolinguistic minimalism seeks a deeper explanation of the design, development and evolution of human language by reducing its core domain to the bare minimum including the set-formation operation Merge. In an attempt to open an avenue of research that may lead to an evolutionarily adequate theory of language, this article makes the following proposals: (i) Merge is the elementary combinatorial device that requires no more decomposition; (ii) the precursor to Merge may be found in the uniquely human capacity for hierarchical object manipulation; (iii) the uniqueness of the human lexicon may also be captured in terms of Merge. Empirical validations of these proposals should constitute one major topic for the biolinguistic program

Derivation without lexical rules

In Krieger and Nerbonne (1992) we showed how to get rid of LEXICAL RULES for DERIVATION, as they are explicated by Pollard and Sag (1987) in HPSG I, Ch. 8.2. We proposed a treatment of derivation not by means of traditional lexical rules but instead in terms of PRINCIPLES, RULES, and LEXICAL ENTRIES entirely in the spirit of HPSG, together with unification-based inheritance of a very sophisticated kind. One major disadvantage of this approach was the employment of complex functions in certain principles. In this paper I first extend the old approach and then show how to eliminate these functional dependencies in the domain of derivational morphology by going back to simpler ones like cons, first, and rest. But this simplification is only achieved if we assume more complex feature structures than the ones described in Krieger and Nerbonne (e.g., by introducing two different SUBCAT features) and by proposing modified versions of the old Constituent Order Principle and the Subcategorization Principle for morphology. In addition, I postulate a hierarchy of affixes which is cross-classified, for instance, according to the effects these affixes contribute to the subcategorization information of a compound word. The structure of the paper is as follows. We start with a very short introduction about the residence of word-formation rules in modern feature-based theories. After that we present our approach to derivational morphology which is distinguished in that it gives up the notion of lexical rule as a single entity (operator). We describe the structure of affixes and words (e.g., which attributes are appropriate?) and introduce the relevant principles and the rule schema of our approach to derivational morphology. The section shows how to reduce functional dependencies to a minimum at the cost of the size of our feature structures. We also present a technique which allows us to state relational dependencies as they are called by HPSG in a functional manner. In the next section we show how the whole treatment works by applying it to tough phenomena from prefixation and suffixation. The section presents many examples, which might serve as a how to guide to a practitioner. After that we explain the idea which will lead us to the affix hierarchy. We will see that the affix hierarchy is inspired by the work of HPSG on structured lexicons (i.e., by the hierarchy of lexical types). A lot of examples will again be given throughout this section. We finish the paper by summarizing our approach and by saying a few words about the topics which we will tackle next

Report on design of new teaching methods and remediation tools for dyslexia

The aim of this work is to provide a review of the remediation therapies that can be used in the rehabilitation of developmental dyslexia; a special emphasis is put on morphological instruction as a promising strategy for compensating the phonological deficits exhibited by dyslexic children, both monolinguals and bilinguals, and enhancing their literacy skills. We will begin our discussion by presenting an overview of developmental dyslexia, discussing its manifestations and its relationships with other developmental disorders, and in particular with Specific Language Impairment. We will then present the results of the studies that we carried out within the European Project AThEME, which confirm the presence of a morphological deficit in dyslexic children, but also point to an advantage in morphological tasks of bilingual children, both dyslexics and typically developing, over their monolingual peers. On the basis of these results, we propose that morphological training could be a viable and effective strategy for the treatment of reading difficulties in both monolingual and bilingual children. We will back this proposal up by presenting the results of three meta- analyses, for a total of 46 studies reviewed, confirming that morphological treatment can lead to enhancements in reading, spelling and literacy-related skills, including phonological and morphological competence, vocabulary development and reading comprehension

Discursive design thinking: the role of explicit knowledge in creative architectural design reasoning

The main hypothesis investigated in this paper is based upon the suggestion that the discursive reasoning in architecture supported by an explicit knowledge of spatial configurations can enhance both design productivity and the intelligibility of design solutions. The study consists of an examination of an architect’s performance while solving intuitively a well-defined problem followed by an analysis of the spatial structure of their design solutions. One group of architects will attempt to solve the design problem logically, rationalizing their design decisions by implementing their explicit knowledge of spatial configurations. The other group will use an implicit form of such knowledge arising from their architectural education to reason about their design acts. An integrated model of protocol analysis combining linkography and macroscopic coding is used to analyze the design processes. The resulting design outcomes will be evaluated quantitatively in terms of their spatial configurations. The analysis appears to show that an explicit knowledge of the rules of spatial configurations, as possessed by the first group of architects can partially enhance their function-driven judgment producing permeable and well-structured spaces. These findings are particularly significant as they imply that an explicit rather than an implicit knowledge of the fundamental rules that make a layout possible can lead to a considerable improvement in both the design process and product. This suggests that by externalizing th

An explanation-driven understanding-directed model for intelligent tutoring systems

Imperial Users onl

A FORMAL REPRESENTATION OF MECHANICAL FUNCTIONS TO SUPPORT PHYSICS-BASED COMPUTATIONAL REASONING IN EARLY MECHANICAL DESIGN

The lack of computational support to the conceptual phase of mechanical engineering design is well recognized. Function-based modeling and thinking is widely recommended in design texts as useful means for describing design concepts and using them in tasks such as solution search, problem decomposition, and design archival. Graph-based function structure models that describe a product as a network of transformative actions of material, energy, and information, are discussed as a potential tool for this purpose, but in the current state of the art, function structures are not formalized as a computational representation. Consequently, no computer tool exists with which a designer can construct grammatically controlled function structure models, explore design ideas by model editing, and perform automated reasoning on the model against the laws of nature to draw analytical inferences on the design. This research presents, verifies, and validates a formal representation of mechanical functions that supports consistent computer-aided modeling of early design and reasoning on those models based on two universal principles of physics: (1) conservation and (2) irreversibility. The representation is complete in three layers. The first layer--the Conservation Layer--is defined with nine entities, five relations, five attributes, and 33 grammar rules that together formalize the construction of function structure graphs and support conservation-based qualitative validation of design concepts. The second layer--the Irreversibility Layer--includes three additional attributes that support both conservation-based and irreversibility-based reasoning at qualitative and quantitative levels. The third layer--the Semantic Layer--is an extension of the previous two, where a vocabulary of nine verbs that describe mechanical devices and physical principles as functions is proposed. This layer supports feature-based modeling and semantic reasoning of function structures. The internal consistency of the representation is verified by logical examination and ontological consistency checking using Protégé-OWL. The coverage of the verbs is examined by constructing descriptive function structure models of a variety of existing physical principles and devices. The research is validated by incorporating the representation in a software tool using an object-oriented language and graphic user-interface, and by using the tool to construct models and demonstrate conservation-based and irreversibility-based reasoning