A survey of qualitative spatial representations

Representation and reasoning with qualitative spatial relations is an important problem in artificial intelligence and has wide applications in the fields of geographic information system, computer vision, autonomous robot navigation, natural language understanding, spatial databases and so on. The reasons for this interest in using qualitative spatial relations include cognitive comprehensibility, efficiency and computational facility. This paper summarizes progress in qualitative spatial representation by describing key calculi representing different types of spatial relationships. The paper concludes with a discussion of current research and glimpse of future work

DNA Computation of Solutions to Edge-Matching Puzzles

The resilient, ancient, and fine-tuned DNA (deoxyribonucleic acid) has inspired many researchers to harness its power for material purposes. In this work, we use synthesized DNA strands to compute the solution to an instance of edge-matching puzzles (EMP), where the challenge is to pack a collection of edge-coloured square tiles on a square board such that all adjacent edges match in colour. We encode tiles with DNA strands and make use of structural, chemical and enzymatic properties of DNA to effectively carry out a brute-force search of the solution to the puzzle. The solution ultimately results as a 2-dimensional DNA lattice encoding the position and orientation of each tile on the solution board. Our approach has been to represent a tile as the union of two half-tiles. This conceptual representation allows for the use of a supremely powerful heuristic: polymerase chain reaction (PCR), which can be inserted at any step of the protocol to selectively amplify certain strands to exponential quantities. Our abstract formalization of half-tiles and the DNA protocol we use to manipulate them have relevance in three ways. First, by solving an instance of the (NP-Complete) EMP problem we make precise characterizations of the processing power of DNA Computing. Second, the 2- dimensional self-assembly of half-tiles is Turing-complete. Thirdly, the 2-dimensional self- assembly of half-tiles can serve as a PCR-powered model for massive nano-scale fabrication of 2- dimensional DNA nano-shapes

On the Combination of Game-Theoretic Learning and Multi Model Adaptive Filters

This paper casts coordination of a team of robots within the framework of game theoretic learning algorithms. In particular a novel variant of fictitious play is proposed, by considering multi-model adaptive filters as a method to estimate other players’ strategies. The proposed algorithm can be used as a coordination mechanism between players when they should take decisions under uncertainty. Each player chooses an action after taking into account the actions of the other players and also the uncertainty. Uncertainty can occur either in terms of noisy observations or various types of other players. In addition, in contrast to other game-theoretic and heuristic algorithms for distributed optimisation, it is not necessary to find the optimal parameters a priori. Various parameter values can be used initially as inputs to different models. Therefore, the resulting decisions will be aggregate results of all the parameter values. Simulations are used to test the performance of the proposed methodology against other game-theoretic learning algorithms.</p