{"title":"Challenges and Applications of Assembly-Level Software Model Checking","authors":"Tilman Mehler","doi":"10.17877/DE290R-8397","DOIUrl":"https://doi.org/10.17877/DE290R-8397","url":null,"abstract":"ion functions φ map states S = (S1, . . . , Sk) to patterns φ(S) = (φ(S1), . . . , φ(Sk)). Pattern databases [CS98] are hash tables for fully explored abstract state spaces, storing with each abstract state the shortest path distance in the abstract space to the abstract goal. They are constructed in a complete traversal of the inverse abstract search space graph. Each distance value stored in the hash table is a lower bound on the solution cost in original space and serves as a heuristic estimate. Different pattern databases can be combined either by adding or maximizing the individual entries for a state. Pattern databases work, if the abstraction function is a homomorphism, so that each path in the original state space has a corresponding one in the abstract state space. In difference to the search in original space, the entire abstract space has to be looked at. As pattern databases are themselves hash tables we apply incremental hashing, too. If we restrict the exploration in STRIPS planning to some certain subset of propositions R ⊆ AP , we generate a planning state space homomorphism φ and an abstract planning state space [Ede01] with states SA ⊆ R. Abstractions of operators o = (P,A, D) are defined as φ(o) = (P ∩ R, A ∩ R,D ∩ R). Multiple pattern databases are composed based on a partition AP = R1 ∪ . . . ∪ Rl and induce abstractions φ1, . . . , φl as well as lookup hash tables PDB1,. . . ,PDBl. Two pattern databases are additive, if the sum of the retrieved values is admissible. One sufficient criterion is the following. For every pair of non-trivial operators o1 and o2 in the abstract spaces according to φ1 and φ2, we have that preimage φ−1 1 (o1) differs from φ −1 2 (o2). For pattern database addressing we use a multivariate variable encoding, namely, SAS+ [Hel04]. 6.7 Hashing Dynamic State Vectors In the previous section, we devised an incremental hashing scheme for static state vectors. This is not directly applicable for program model checkers, as they operate on dynamic and structured states. Dynamic means, that the size of a vector may change. For example, a program can dynamically allocate new memory regions. Structured means, that the state is separated in several subvectors rather than a single big vector. In StEAM for example, the stacks, machines, variable sections and the lock/memory pools constitute subvectors which together form a global state vector. In the following, we extend the incremental hashing scheme from the last section to be applicable for dynamic and distributed states. For dynamic vectors, components may be inserted at arbitrary positions. We will regard dynamic vectors as the equivalent of strings over an alphabet Σ. In the following, for two vectors a and b, let a, b denote the concatenation of a and b. For 100 CHAPTER 6. HASHING example, for a = (0, 8) and b = (15), we define a, b = (0, 8, 15). We define four general lemmas for the hash function h as used in Rabin-Karp hashing (cf. Section 6.5.1). Lemmas 1","PeriodicalId":165875,"journal":{"name":"Künstliche Intell.","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133444859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Learning to Win: Case-Based Plan Selection in a Real-Time Strategy Game","authors":"D. Aha, M. Molineaux, M. Ponsen","doi":"10.1007/11536406_4","DOIUrl":"https://doi.org/10.1007/11536406_4","url":null,"abstract":"","PeriodicalId":165875,"journal":{"name":"Künstliche Intell.","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114439963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"KiRo - A Table Soccer Robot Ready for the Market","authors":"T. Weigel","doi":"10.1109/ROBOT.2005.1570776","DOIUrl":"https://doi.org/10.1109/ROBOT.2005.1570776","url":null,"abstract":"This paper presents the autonomous table soccer robot KiRo. KiRo provides a competitive challenge for even advanced human players and is well suited as a toy or even as a training partner for professional players. Moreover, the table soccer game represents a demanding testbed for evaluating a multitude of techniques and approaches in the fields of robotics and artificial intelligence. KiRo has reached a technically mature level and will be commercially available by January 2005.","PeriodicalId":165875,"journal":{"name":"Künstliche Intell.","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126241326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Dorigo, E. Tuci, R. Groß, V. Trianni, T. H. Labella, Shervin Nouyan, C. Ampatzis, J. Deneubourg, G. Baldassarre, S. Nolfi, F. Mondada, D. Floreano, L. Gambardella
{"title":"The SWARM-BOTS Project","authors":"M. Dorigo, E. Tuci, R. Groß, V. Trianni, T. H. Labella, Shervin Nouyan, C. Ampatzis, J. Deneubourg, G. Baldassarre, S. Nolfi, F. Mondada, D. Floreano, L. Gambardella","doi":"10.1007/978-3-540-30552-1_4","DOIUrl":"https://doi.org/10.1007/978-3-540-30552-1_4","url":null,"abstract":"","PeriodicalId":165875,"journal":{"name":"Künstliche Intell.","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133769643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Knowledge Portals","authors":"Steffen Staab","doi":"10.3115/1118220.1118221","DOIUrl":"https://doi.org/10.3115/1118220.1118221","url":null,"abstract":"Knowledge portals provide views onto domainspecific information on the World Wide Web, thus facilitating their users to find relevant, domainspecific information. The construction of intelligent access and the provisioning of information to knowledge portals, however, remained an ad hoc task requiring extensive manual editing and maintenance by the knowledge portal providers. In order to diminish these efforts we use ontologies as a conceptual backbone for providing, accessing and structuring information in a comprehensive approach for building and maintaining knowledge portals. We have built several experimental and one commercial knowledge portal for knowledge management tasks such as skill management and corporate history analysis that show how our approach is used in practice. This practice, however, has exhibited a number bottlenecks, many of which could be avoided or at least diminished by Human Language Technology. We have used HLT in order to reduce the costs of ontology engineering and in order to narrow the gap between finding knowledge in texts and providing it to the portal.","PeriodicalId":165875,"journal":{"name":"Künstliche Intell.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129006932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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