685 research outputs found

    An Algorithmic Analysis of the Honey-Bee Game

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    The Honey-Bee game is a two-player board game that is played on a connected hexagonal colored grid or (in a generalized setting) on a connected graph with colored nodes. In a single move, a player calls a color and thereby conquers all the nodes of that color that are adjacent to his own current territory. Both players want to conquer the majority of the nodes. We show that winning the game is PSPACE-hard in general, NP-hard on series-parallel graphs, but easy on outerplanar graphs. In the solitaire version, the goal of the single player is to conquer the entire graph with the minimum number of moves. The solitaire version is NP-hard on trees and split graphs, but can be solved in polynomial time on co-comparability graphs.Comment: 20 pages, 9 figure

    The systematicity challenge to anti-representational dynamicism

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    After more than twenty years of representational debate in the cognitive sciences, anti-representational dynamicism may be seen as offering a rival and radically new kind of explanation of systematicity phenomena. In this paper, I argue that, on the contrary, anti-representational dynamicism must face a version of the old systematicity challenge: either it does not explain systematicity, or else, it is just an implementation of representational theories. To show this, I present a purely behavioral and representation-free account of systematicity. I then consider a case of insect sensorimotor systematic behavior: communicating behavior in honey bees. I conclude that anti-representational dynamicism fails to capture the fundamental trait of systematic behaviors qua systematic, i.e., their involving exercises of the same behavioral capacities. I suggest, finally, a collaborative strategy in pursuit of a rich and powerful account of this central phenomenon of high cognition at all levels of explanation, including the representational level

    Extremal properties of flood-filling games

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    The problem of determining the number of "flooding operations" required to make a given coloured graph monochromatic in the one-player combinatorial game Flood-It has been studied extensively from an algorithmic point of view, but basic questions about the maximum number of moves that might be required in the worst case remain unanswered. We begin a systematic investigation of such questions, with the goal of determining, for a given graph, the maximum number of moves that may be required, taken over all possible colourings. We give several upper and lower bounds on this quantity for arbitrary graphs and show that all of the bounds are tight for trees; we also investigate how much the upper bounds can be improved if we restrict our attention to graphs with higher edge-density.Comment: Final version, accepted to DMTC

    The complexity of Free-Flood-It on 2xn boards

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    We consider the complexity of problems related to the combinatorial game Free-Flood-It, in which players aim to make a coloured graph monochromatic with the minimum possible number of flooding operations. Our main result is that computing the length of an optimal sequence is fixed parameter tractable (with the number of colours present as a parameter) when restricted to rectangular 2xn boards. We also show that, when the number of colours is unbounded, the problem remains NP-hard on such boards. This resolves a question of Clifford, Jalsenius, Montanaro and Sach (2010)

    Gaming security by obscurity

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    Shannon sought security against the attacker with unlimited computational powers: *if an information source conveys some information, then Shannon's attacker will surely extract that information*. Diffie and Hellman refined Shannon's attacker model by taking into account the fact that the real attackers are computationally limited. This idea became one of the greatest new paradigms in computer science, and led to modern cryptography. Shannon also sought security against the attacker with unlimited logical and observational powers, expressed through the maxim that "the enemy knows the system". This view is still endorsed in cryptography. The popular formulation, going back to Kerckhoffs, is that "there is no security by obscurity", meaning that the algorithms cannot be kept obscured from the attacker, and that security should only rely upon the secret keys. In fact, modern cryptography goes even further than Shannon or Kerckhoffs in tacitly assuming that *if there is an algorithm that can break the system, then the attacker will surely find that algorithm*. The attacker is not viewed as an omnipotent computer any more, but he is still construed as an omnipotent programmer. So the Diffie-Hellman step from unlimited to limited computational powers has not been extended into a step from unlimited to limited logical or programming powers. Is the assumption that all feasible algorithms will eventually be discovered and implemented really different from the assumption that everything that is computable will eventually be computed? The present paper explores some ways to refine the current models of the attacker, and of the defender, by taking into account their limited logical and programming powers. If the adaptive attacker actively queries the system to seek out its vulnerabilities, can the system gain some security by actively learning attacker's methods, and adapting to them?Comment: 15 pages, 9 figures, 2 tables; final version appeared in the Proceedings of New Security Paradigms Workshop 2011 (ACM 2011); typos correcte

    Computational Thinking Equity in Elementary Classrooms: What Third-Grade Students Know and Can Do

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    The Computer Science Teachers Association has asserted that computational thinking equips students with essential critical thinking which allows them to conceptualize, analyze, and solve more complex problems. These skills are applicable to all content area as students learn to use strategies, ideas, and technological practices more effectively as digital natives. This research examined over 200 elementary students’ pre- and posttest changes in computational thinking from a 10-week coding program using adapted lessons from code.org’s Blockly programming language and CSUnplugged that were delivered as part of the regular school day. Participants benefited from early access to computer science (CS) lessons with increases in computational thinking and applying coding concepts to the real world. Interviews from participants included examples of CS connections to everyday life and interdisciplinary studies at school. Thus, the study highlights the importance of leveraging CS access in diverse elementary classrooms to promote young students’ computational thinking; motivation in CS topics; and the learning of essential soft-skills such as collaboration, persistence, abstraction, and creativity to succeed in today’s digital world
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