Biologically inspired computing
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Recent papers in Biologically inspired computing
Software systems are becoming ever more complex, as the capabilities of the software upon which they are based increase. To develop software that is manageable, we must look for novel sources of inspiration, rather than requiring an... more
This is the readable introductory version of Global Workspace Theory, published in 1997 in the Journal of Consciousness Studies. The Oxford University Press book of that year provides an easy book-length introduction. Since 1997 our... more
Introduction to Algorithms for Data Mining and Machine Learning (book) introduces the essential ideas behind all key algorithms and techniques for data mining and machine learning, along with optimization techniques. Its strong formal... more
The textbook is available in hard-copy version (in Serbian language) primary for our MSc and PhD students to learn and investigate modern scientific disciplines in domain of intelligent manufacturing systems and processes development.... more
The growing complexity of real-world problems has motivated computer scientists to search for efficient problem-solving methods. Evolutionary Computation and Swarm Intelligence metaheuristics are outstanding examples that nature has been... more
ABSRACT: Design methodologies have radically shifted our conception of the design process, as well as our understanding of geometrical forms as a function of performance instead of finite positions in space. However, the materials... more
Many optimization problems in science and engineering are highly nonlinear, and thus require sophisticated optimization techniques to solve. Traditional techniques such as gradient-based algorithms are mostly local search methods, and... more
This work investigates the parallelization of the Artificial Bee Colony Algorithm. Besides a sequential version enhanced with local search, we compare three parallel models: master-slave, multi-hive with migrations, and hybrid... more
This work presents an integrated simulation system for development of modular robotic locomotion patterns. Using graphical configuration interfaces users can create robots, attach sensors, create and assign actuation algorithms, build an... more
UTS Bio Inspired Computation, Bio Inspired Computation, UTS Komputasi Berbasis Biologi, Komputasi Berbasis Biologi, Komputasi Biologi, Bioinformatika, Bioinformatics, UTS Bio, Informatika, Teknik Informatika, Universitas... more
This paper reports the hybridization of the artificial bee colony (ABC) and a genetic algorithm (GA), ina hierarchical topology, a step ahead of a previous work. We used this parallel approach for solving theprotein structure prediction... more
Lifelong learning is a long-standing aim for artificial agents that act in dynamic environments in which an agent needs to accumulate knowledge incrementally without forgetting previously learned representations. Contemporary methods for... more
In an attempt to provide a unified account for a vast literature discussing a multiplicity of selves, Shaun Gallagher (2013) has proposed a pattern theory of self. Subsequent discussion on this account has led to a concern that the... more
Biocomputing is a recently growing and highly interdisciplinary field of research that investigates models and computational techniques inspired by biology and related sciences. Here, cyclic behavior (redox cycling) of purified... more
This article reinterprets the Global Workspace theory in the form of a coherent model. The model is initial and simple. It interconnects the Working Memory and the Long Therm Memory using the graph theory. The model can be used for... more
This paper develops PeSeeD, a new metaheuristic algorithm for finding optimal spaced seed. Sequences matching is a hot topic in bio-informatics, which is used in many applications such as understanding the functional, structural, or... more
Although inspired by the biological aspect, the concept of autonomic computing is emblematic of the diversity of solutions that propose a self-governance of systems from high-level objectives. From the human point of view, the autonomic... more
Purpose – The purpose of this paper is to study the slime mould Physarum polycephalum as an ideal biological substrate for transport networks. When presented with several sources of nutrients the slime mould propagates colonises the... more
In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of... more
Abstract shown in the journal article. Please note that "the frame problem" is a general challenge in AI/robotics as well as in computational neurobiology. Broadly speaking, as a robot drives outside of a familiar space, like a... more
It is well known that, in nature, populations are dynamic in space and time. This means that the size of populations oscillate across their habitats over time. This work uses the concepts of habitats, ecological relationships, ecological... more
Although inspired by the biological aspect, the concept of autonomic computing is emblematic of the diversity of solutions that propose a self-governance of systems from high-level objectives. From the human point of view, the autonomic... more
One of the more interesting concepts being postulated for next gen power plants, is the notion of highly resilient and survivable I&C systems. While resilience and survivability are “cross system attributes”, resilience and robustness... more