Biologically inspired information theory: Adaptation through construction of external reality models by living systems

2015 ◽  
Vol 119 (3) ◽  
pp. 634-648 ◽  
Author(s):  
Toshiyuki Nakajima
Keyword(s):  
Information Theory ◽  
Living Systems ◽  
Biologically Inspired ◽  
External Reality

scholarly journals On Crashing the Barrier of Meaning in Artificial Intelligence

AI Magazine ◽  
2020 ◽  
Vol 41 (2) ◽  
pp. 86-92 ◽  
Author(s):  
Melanie Mitchell
Keyword(s):  
Artificial Intelligence ◽  
Information Theory ◽  
Animal Behavior ◽  
Developmental Psychology ◽  
Living Systems ◽  
Santa Fe ◽  
Dawn Song ◽  
Artificial Intelligence Systems

In 1986, the mathematician and philosopher Gian-Carlo Rota wrote, “I wonder whether or when artificial intelligence will ever crash the barrier of meaning” (Rota 1986). Here, the phrase “barrier of meaning” refers to a belief about humans versus machines: Humans are able to actually understand the situations they encounter, whereas even the most advanced of today’s artificial intelligence systems do not yet have a humanlike understanding of the concepts that we are trying to teach them. This lack of understanding may underlie current limitations on the generality and reliability of modern artificial intelligence systems. In October 2018, the Santa Fe Institute held a three-day workshop, organized by Barbara Grosz, Dawn Song, and myself, called Artificial Intelligence and the Barrier of Meaning. Thirty participants from a diverse set of disciplines — artificial intelligence, robotics, cognitive and developmental psychology, animal behavior, information theory, and philosophy, among others — met to discuss questions related to the notion of understanding in living systems and the prospect for such understanding in machines. In the hope that the results of the workshop will be useful to the broader community, this article summarizes the main themes of discussion and highlights some of the ideas developed at the workshop.

scholarly journals On the Scales of Selves: Information, Life, and Buddhist Philosophy

2021 ◽  
Author(s):  
Carlos Gershenson
Keyword(s):  
Information Theory ◽  
Buddhist Philosophy ◽  
Living Systems

When we attempt to define life, we tend to refer to individuals, those that are alive. But these individuals might be cells, organisms, colonies... ecosystems? We can describe living systems at different scales. Which ones might be the best ones to describe different selves? I explore this question using concepts from information theory, ALife, and Buddhist philosophy. After brief introductions, I review the implications of changing the scale of observation, and how this affects our understanding of selves at different structural, temporal, and informational scales. The conclusion is that there is no single ``best'' scale for a self, as this will depend on the scale at which decisions must be made. Different decisions, different scales.

A roadmap for Living Machines research

2018 ◽  
Author(s):  
Nathan F. Lepora ◽  
Paul F. M. J. Verschure ◽  
Tony J. Prescott
Keyword(s):  
Biological Systems ◽  
Living Systems ◽  
Future Research ◽  
Scientific Policy ◽  
Biologically Inspired ◽  
Policy Makers ◽  
Research And Innovation ◽  
Current Trends

This roadmap identifies current trends in biomimetic and biohybrid systems together with their implications for future research and innovation. Important questions include the scale at which these systems are defined, the types of biological systems addressed, the kind of principles sought, the differences between biologically based and biologically inspired approaches, the role in the understanding of living systems, relevant application domains, common benchmarks, the relation to other fields, and developments on the horizon. We interviewed and collated answers from experts who have been involved a series of events organized by the Convergent Science Network. These answers were then collated into themes of research. Overall, we see a field rapidly expanding in influence and impact. As such, this report will provide information to researchers and scientific policy makers on contemporary biomimetics and its future, together with pointers to further reading on relevant topics within this handbook.

Mechanoevolution: The Possibility of Deeper Connections Between Information Theory and the Second Law

2010 ◽  
Author(s):  
Bradley E. Layton
Keyword(s):  
Information Theory ◽  
Entropy Production ◽  
Specific Energy ◽  
Physical Property ◽  
Living Systems ◽  
Second Law ◽  
Local Entropy ◽  
Technological Systems ◽  
Hand Tools ◽  
Formal Relationship

Entropy, S is an extensive physical property with dimensions of energy per Kelvin. Information, I is an extensive mathematical metric with units of bits. If we consider discrete living systems such as individual organisms as well as discrete technological systems such as hand tools, automobiles, and computers as systems that maintain both a quantifiable specific energy throughput, φ and a quantifiable information throughput, I˙m at the expense of entropy production, S˙, we can then begin to build a formal relationship among these three variables within organic, synthetic and hybrid systems. The combination of mass-specific energy and information throughput within a system results in a local partitioning of entropy: local entropy diminution causes global entropy acceleration. In general, as the symbioses between humans and machines become more tightly bound through a process termed “mechanoevolution,” the respective rates of information throughput, energy throughput, and thus entropy production accelerate towards a yet unknown limit.

scholarly journals Living Systems Escape Solipsism by Inverse Causality to Manage the Probability Distribution of Events

Philosophies ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 11
Author(s):  
Toshiyuki Nakajima
Keyword(s):  
Probability Distribution ◽  
Open Systems ◽  
Living Systems ◽  
System Model ◽  
Signal Transducer ◽  
Data Sequence ◽  
External Reality ◽  
Internal Structures ◽  
Subject Of Cognition ◽  
Algorithmic Process

The external worlds do not objectively exist for living systems because these worlds are unknown from within systems. How can they escape solipsism to survive and reproduce as open systems? Living systems must construct their hypothetical models of external entities in the form of their internal structures to determine how to change states (i.e., sense and act) appropriately to achieve a favorable probability distribution of the events they experience. The model construction involves the generation of symbols referring to external entities. This paper attempts to provide a new view that living systems are an inverse-causality operator. Inverse causality (IC) is an algorithmic process that generates symbols referring to external reality states based on a given data sequence. For applying this logical model involving if–then entailments to living systems involving material interactions, the cognizers-system model was employed to represent the IC process; here, living systems were modeled as a subject of cognition and action. A focal subject system is described as a cognizer composed of sub-cognizers, such as a sensor, a signal transducer, and an effector. Analysis using this model proposes that living systems invented the “measurers” for conducting IC operations through their evolution.

scholarly journals Information theory, predictability and the emergence of complex life

2018 ◽  
Vol 5 (2) ◽  
pp. 172221 ◽  
Author(s):  
Luís F. Seoane ◽  
Ricard V. Solé
Keyword(s):  
Information Theory ◽  
Cognitive Complexity ◽  
Formal Model ◽  
Life Forms ◽  
Living Systems ◽  
Environmental Cues ◽  
Complex Structures ◽  
Obvious Advantage ◽  
Successive Generations ◽  
Different Levels

Despite the obvious advantage of simple life forms capable of fast replication, different levels of cognitive complexity have been achieved by living systems in terms of their potential to cope with environmental uncertainty. Against the inevitable cost associated with detecting environmental cues and responding to them in adaptive ways, we conjecture that the potential for predicting the environment can overcome the expenses associated with maintaining costly, complex structures. We present a minimal formal model grounded in information theory and selection, in which successive generations of agents are mapped into transmitters and receivers of a coded message. Our agents are guessing machines and their capacity to deal with environments of different complexity defines the conditions to sustain more complex agents.

Levels of Description: A Novel Approach to Dynamical Hierarchies

2005 ◽  
Vol 11 (4) ◽  
pp. 459-472 ◽  
Author(s):  
Simon McGregor ◽  
Chrisantha Fernando
Keyword(s):  
Information Theory ◽  
Dynamical Systems ◽  
Empirical Studies ◽  
State Dependence ◽  
Partial Ordering ◽  
Living Systems ◽  
Novel Approach ◽  
Dependence Criterion

We present a novel formal interpretation of dynamical hierarchies based on information theory, in which each level is a near-state-determined system, and levels are related to one another in a partial ordering. This reformulation moves away from previous definitions, which have considered unique hierarchies of structures or objects arranged in aggregates. Instead, we consider hierarchies of dynamical systems: these are more suited to describing living systems, which are not mere aggregates, but organizations. Transformations from lower to higher levels in a hierarchy are redescriptions that lose information. There are two criteria for partial ordering. One is a state-dependence criterion enforcing predictability within a level. The second is a distinctness criterion enforcing the idea that the higher-level description must do more than just throw information away. We hope this will be a useful tool for empirical studies of both computational and physical dynamical hierarchies.

On the Scales of Selves: Information, Life, and Buddhist Philosophy

2021 ◽  
Author(s):  
Carlos Gershenson
Keyword(s):  
Information Theory ◽  
Buddhist Philosophy ◽  
Living Systems

When we attempt to define life, we tend to refer to individuals, those that are alive. But these individuals might be cells, organisms, colonies... ecosystems? We can describe living systems at different scales. Which ones might be the best ones to describe different selves? I explore this question using concepts from information theory, ALife, and Buddhist philosophy. After brief introductions, I review the implications of changing the scale of observation, and how this affects our understanding of selves at different structural, temporal, and informational scales. The conclusion is that there is no ``best'' scale for a self, as this will depend on the scale at which decisions must be made. Different decisions, different scales.

scholarly journals What Is Consciousness? Integrated Information vs. Inference

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 1032
Author(s):  
James E. Cooke
Keyword(s):  
Information Theory ◽  
Causal Power ◽  
Living Systems ◽  
Conscious Perception ◽  
Conscious Living ◽  
Naturalistic Account ◽  
High Level ◽  
Mirror Theory ◽  
Integrated Information Theory ◽  
Integrated Information

Any successful naturalistic account of consciousness must state what consciousness is, in terms that are compatible with the rest of our naturalistic descriptions of the world. Integrated Information Theory represents a pioneering attempt to do just this. This theory accounts for the core features of consciousness by holding that there is an equivalence between the phenomenal experience associated with a system and its intrinsic causal power. The proposal, however, fails to provide insight into the qualitative character of consciousness and, as a result of its proposed equivalence between consciousness and purely internal dynamics, into the intentional character of conscious perception. In recent years, an alternate group of theories has been proposed that claims consciousness to be equivalent to certain forms of inference. One such theory is the Living Mirror theory, which holds consciousness to be a form of inference performed by all living systems. The proposal of consciousness as inference overcomes the shortcomings of Integrated Information Theory, particularly in the case of conscious perception. A synthesis of these two perspectives can be reached by appreciating that conscious living systems are self-organising in nature. This mode of organization requires them to have a high level of integration. From this perspective, we can understand consciousness as being dependent on a system possessing non-trivial amounts of integrated information while holding that the process of inference performed by the system is the fact of consciousness itself.

Sign in / Sign up

Export Citation Format

Share Document