345,082 research outputs found
Natural Computing and Beyond
This book contains the joint proceedings of the Winter School of Hakodate (WSH) 2011 held in Hakodate, Japan, March 15–16, 2011, and the 6th International Workshop on Natural Computing (6th IWNC) held in Tokyo, Japan, March 28–30, 2012, organized by the Special Interest Group of Natural Computing (SIG-NAC), the Japanese Society for Artificial Intelligence (JSAI). This volume compiles refereed contributions to various aspects of natural computing, ranging from computing with slime mold, artificial chemistry, eco-physics, and synthetic biology, to computational aesthetics
Natural Computing and Beyond
This book contains the joint proceedings of the Winter School of Hakodate (WSH) 2011 held in Hakodate, Japan, March 15–16, 2011, and the 6th International Workshop on Natural Computing (6th IWNC) held in Tokyo, Japan, March 28–30, 2012, organized by the Special Interest Group of Natural Computing (SIG-NAC), the Japanese Society for Artificial Intelligence (JSAI). This volume compiles refereed contributions to various aspects of natural computing, ranging from computing with slime mold, artificial chemistry, eco-physics, and synthetic biology, to computational aesthetics
Credal Valuation Networks for Machine Reasoning Under Uncertainty
Contemporary undertakings provide limitless opportunities for widespread
application of machine reasoning and artificial intelligence in situations
characterised by uncertainty, hostility and sheer volume of data. The paper
develops a valuation network as a graphical system for higher-level fusion and
reasoning under uncertainty in support of the human operators. Valuations,
which are mathematical representation of (uncertain) knowledge and collected
data, are expressed as credal sets, defined as coherent interval probabilities
in the framework of imprecise probability theory. The basic operations with
such credal sets, combination and marginalisation, are defined to satisfy the
axioms of a valuation algebra. A practical implementation of the credal
valuation network is discussed and its utility demonstrated on a small scale
example.Comment: 16 pages, 3 figure
Novel Artificial Human Optimization Field Algorithms - The Beginning
New Artificial Human Optimization (AHO) Field Algorithms can be created from
scratch or by adding the concept of Artificial Humans into other existing
Optimization Algorithms. Particle Swarm Optimization (PSO) has been very
popular for solving complex optimization problems due to its simplicity. In
this work, new Artificial Human Optimization Field Algorithms are created by
modifying existing PSO algorithms with AHO Field Concepts. These Hybrid PSO
Algorithms comes under PSO Field as well as AHO Field. There are Hybrid PSO
research articles based on Human Behavior, Human Cognition and Human Thinking
etc. But there are no Hybrid PSO articles which based on concepts like Human
Disease, Human Kindness and Human Relaxation. This paper proposes new AHO Field
algorithms based on these research gaps. Some existing Hybrid PSO algorithms
are given a new name in this work so that it will be easy for future AHO
researchers to find these novel Artificial Human Optimization Field Algorithms.
A total of 6 Artificial Human Optimization Field algorithms titled "Human
Safety Particle Swarm Optimization (HuSaPSO)", "Human Kindness Particle Swarm
Optimization (HKPSO)", "Human Relaxation Particle Swarm Optimization (HRPSO)",
"Multiple Strategy Human Particle Swarm Optimization (MSHPSO)", "Human Thinking
Particle Swarm Optimization (HTPSO)" and "Human Disease Particle Swarm
Optimization (HDPSO)" are tested by applying these novel algorithms on Ackley,
Beale, Bohachevsky, Booth and Three-Hump Camel Benchmark Functions. Results
obtained are compared with PSO algorithm.Comment: 25 pages, 41 figure
A Hybrid Reasoning Model for “Whole and Part” Cardinal Direction Relations
We have shown how the nine tiles in the projection-based model for cardinal directions can be partitioned into sets based on horizontal and vertical constraints (called Horizontal and Vertical Constraints Model) in our previous papers (Kor and Bennett, 2003 and 2010). In order to come up with an expressive hybrid model for direction relations between two-dimensional single-piece regions (without holes), we integrate the well-known RCC-8 model with the above-mentioned model. From this expressive hybrid model, we derive 8 basic binary relations and 13 feasible as well as jointly exhaustive relations for the x- and y-directions, respectively. Based on these basic binary relations, we derive two separate composition tables for both the expressive and weak direction relations. We introduce a formula that can be used for the computation of the composition of expressive and weak direction relations between “whole or part” regions. Lastly, we also show how the expressive hybrid model can be used to make several existential inferences that are not possible for existing models
Allocation in Practice
How do we allocate scarcere sources? How do we fairly allocate costs? These
are two pressing challenges facing society today. I discuss two recent projects
at NICTA concerning resource and cost allocation. In the first, we have been
working with FoodBank Local, a social startup working in collaboration with
food bank charities around the world to optimise the logistics of collecting
and distributing donated food. Before we can distribute this food, we must
decide how to allocate it to different charities and food kitchens. This gives
rise to a fair division problem with several new dimensions, rarely considered
in the literature. In the second, we have been looking at cost allocation
within the distribution network of a large multinational company. This also has
several new dimensions rarely considered in the literature.Comment: To appear in Proc. of 37th edition of the German Conference on
Artificial Intelligence (KI 2014), Springer LNC
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