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Global control for partial deduction through characteristic atoms and global trees
, 1995
"... Abstract. Recently, considerable advances have been made in the (online) control of logic program specialisation. A clear conceptual distinction has been established between local and global control and on both levels concrete strategies as well as general frameworks have been proposed. For global c ..."
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Cited by 48 (21 self)
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Abstract. Recently, considerable advances have been made in the (online) control of logic program specialisation. A clear conceptual distinction has been established between local and global control and on both levels concrete strategies as well as general frameworks have been proposed. For global control in particular, recent work has developed concrete techniques based on the preservation of characteristic trees (limited, however, by a given, arbitrary depth bound) to obtain a very precise control of polyvariance. On the other hand, the concept of an mtree has been introduced as a refined way to trace “relationships ” of partially deduced atoms, thus serving as the basis for a general framework within which global termination of partial deduction can be ensured in a non ad hoc way. Blending both, formerly separate, contributions, in this paper, we present an elegant and sophisticated technique to globally control partial deduction of normal logic programs. Leaving unspecified the specific local control one may wish to plug in, we develop a concrete global control strategy combining the use of characteristic atoms and trees with global (m)trees. We thus obtain partial deduction that always terminates in an elegant, non ad hoc way, while providing excellent specialisation as well as finegrained (but reasonable) polyvariance. We conjecture that a similar approach may contribute to improve upon current (online) control strategies for functional program transformation methods such as (positive) supercompilation. 1
A TwoLevel BDIAgent Model for Theory of Mind and its Use
 in Social Manipulation. In: Proc. of the AISB 2007 Workshop on Mindful Environments
, 2007
"... Abstract. This paper introduces a formal BDIbased agent model for Theory of Mind. The model uses BDIconcepts to describe the reasoning process of an agent that reasons about the reasoning process of another agent, which is also based on BDIconcepts. A case study illustrates how the model can be u ..."
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Cited by 23 (16 self)
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Abstract. This paper introduces a formal BDIbased agent model for Theory of Mind. The model uses BDIconcepts to describe the reasoning process of an agent that reasons about the reasoning process of another agent, which is also based on BDIconcepts. A case study illustrates how the model can be used for social manipulation. This case study addresses the scenario of a manager that reasons about the task avoiding behaviour of his employee. For this scenario, a number of simulation experiments have been performed, and some of their results are discussed. 1
To Parse or Not To Parse
 Logic Program Synthesis and Transformation. Proceedings of LOPSTR’97, LNCS 1463
, 1997
"... . In this paper, we reconsider the problem of specialising the vanilla meta interpreter through fully automatic and completely general partial deduction techniques. In particular, we study how the homeomorphic embedding relation guides specialisation of the interpreter. We focus on the socalled ..."
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Cited by 17 (6 self)
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. In this paper, we reconsider the problem of specialising the vanilla meta interpreter through fully automatic and completely general partial deduction techniques. In particular, we study how the homeomorphic embedding relation guides specialisation of the interpreter. We focus on the socalled parsing problem, i.e. removing all parsing overhead from the program, and demonstrate that further refinements in the control of general partial deduction are necessary to properly deal with it. In particular, we modify local control on the basis of information imported from the global level. The resulting control strategy, while remaining fully general, leads to excellent specialisation of vanilla like meta programs. Parsing is always specialised, but  appropriately, as we will show  not always completely removed. As a concrete application, we subject an extended vanilla meta interpreter capable of dealing with compositions of programs to our techniques, showing we equal or surpass results obtained through a more ad hoc approach. 1
Black hole search in asynchronous rings using tokens
 In 6 th Conference on Algorithms and Complexity (CIAC ’06
, 2006
"... Abstract. A black hole is a highly harmful host that disposes of visiting agents upon their arrival. It is known that it is possible for a team of mobile agents to locate a black hole in an asynchronous ring network if each node is equipped with a whiteboard of at least O(log n) dedicated bits of st ..."
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Cited by 12 (5 self)
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Abstract. A black hole is a highly harmful host that disposes of visiting agents upon their arrival. It is known that it is possible for a team of mobile agents to locate a black hole in an asynchronous ring network if each node is equipped with a whiteboard of at least O(log n) dedicated bits of storage. In this paper, we consider the less powerful token model: each agent has has available a bounded number of tokens that can be carried, placed on a node or removed from it. All tokens are identical (i.e., indistinguishable) and no other form of communication or coordination is available to the agents. We first of all prove that a team of two agents is sufficient to locate the black hole in finite time even in this weaker coordination model. Furthermore, we prove that this can be accomplished using only O(n log n) moves in total, which is optimal, the same as with whiteboards. Finally, we show that to achieve this result the agents need to use only O(1) tokens each.
LOWER BOUNDS FOR AGNOSTIC LEARNING VIA APPROXIMATE RANK
"... Abstract. We prove that the concept class of disjunctions cannot be pointwise approximated by linear combinations of any small set of arbitrary realvalued functions. That is, suppose that there exist functions φ1,..., φr: {−1, 1} n → R with the property that every disjunction f on n variables has ‖ ..."
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Cited by 4 (1 self)
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Abstract. We prove that the concept class of disjunctions cannot be pointwise approximated by linear combinations of any small set of arbitrary realvalued functions. That is, suppose that there exist functions φ1,..., φr: {−1, 1} n → R with the property that every disjunction f on n variables has ‖f − ∑r i=1 αiφi‖ ∞ � 1/3 for some reals α1,..., αr. We prove that then r � exp{Ω ( √ n)}, which is tight. We prove an incomparable lower bound for the concept class of decision lists. For the concept class of majority functions, we obtain a lower bound of Ω(2n /n), which almost meets the trivial upper bound of 2n for any concept class. These lower bounds substantially strengthen and generalize the polynomial approximation lower bounds of Paturi (1992) and show that the regressionbased agnostic learning algorithm of Kalai et al. (2005) is optimal.