scholarly journals Human-Centric Functional Modeling and Evolutionary Biology

2021 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Climate Change ◽  
Problem Solving ◽  
General Problem ◽  
Biological System ◽  
Evolutionary Biology ◽  
Functional Modeling ◽  
State Spaces ◽  
Wide Range ◽  
Definition Of ◽  
Biological Organisms

The newly emerging science of Human-Centric Functional Modeling provides an approach towards modeling biological and other systems that is hypothesized to maximize human capacity to understand and navigate complexity in those systems. This paper provide an overview exploring how Human-Centric Functional Modeling might be applied in evolutionary biology, and how this increase in capacity to understand the complexity that organisms have evolved into might be achieved. The broader usefulness of Human-Centric Functional Modeling is that it provides a simple mathematical definition of what constitutes a biological system, defines the problem-solving domain of any biological system in terms of abstract mathematical spaces, and provides an expression defining general problem-solving ability in any such domain. This enables it to be seen that all systems with general problem-solving ability in their own domain are potentially an abstraction of a single mathematical pattern of adaptive problem-solving that might apply to all domains. From this perspective nature has already potentially solved problems in biological organisms that can be represented in some abstract functional state spaces as the same general problem that must be solved to address problems in a wide range of other systems, including existential challenges from poverty to climate change, where Human-Centric Functional Modeling enables it to be seen that not only can nature’s solutions be copied, but that nature has demonstrated its solutions to have worked for hundreds of millions of years.

scholarly journals Using Systems Thinking to Exponentially Increase Impact

2021 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Climate Change ◽  
Problem Solving ◽  
Systems Thinking ◽  
General Problem ◽  
Collective Intelligence ◽  
General Intelligence ◽  
Functional Modeling ◽  
Artificial General Intelligence ◽  
Exponential Increase

This paper explores how Human-Centric Functional Modeling might provide a method of systems thinking that in combination with models of Artificial General Intelligence and General Collective Intelligence developed using the approach, creates the opportunity to exponentially increase impact on targeted outcomes of collective activities, including research in a wide variety of disciplines as well as activities involved in addressing the various existential challenges facing mankind. Whether exponentially increasing the speed and scale of progress in research disciplines such as physics or medicine, or whether exponentially increasing capacity to solve existential challenges such as poverty or climate change, this paper explores why gaining the capacity to reliably solve such challenges might require this exponential increase in general problem-solving ability, why this exponential increase in ability might be reliably achievable through this approach, and why solving our most existential challenges might be reliably unachievable otherwise.

scholarly journals Human-Centric Functional Modeling of Biocomputers

2021 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Problem Solving ◽  
General Problem ◽  
Functional Modeling ◽  
Biological Computing ◽  
Functional Models ◽  
Multiple Domains ◽  
The Impact

This paper explores how the technique of Human-Centric Functional Modeling might potentially be used to represent a broad subset of proposed implementations of biocomputing with anywhere from narrow to general problem-solving ability within a given domain, or across multiple domains, and how such functional models might be implemented by libraries of biological computing mechanisms. This paper also explores the insights to be gained from modeling biocomputers this way, and how Human-Centric Functional Modeling might significantly accelerate research and increase the impact of research in biocomputing through significantly increasing capacity for reuse of both biocomputing hardware and software.

scholarly journals Cognitive Computing and its Relationship to Computing Methods and Advanced Computing from a Functional Modeling Perspective

2020 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Problem Solving ◽  
General Problem ◽  
Collective Intelligence ◽  
Computing Methods ◽  
Modeling Technique ◽  
Human Cognition ◽  
Cognitive Computing ◽  
Functional Modeling ◽  
Semantic Modeling ◽  
Advanced Computing

Recent advances in modeling human cognition have resulted in what is suggested to be the first model of Artificial General Intelligence (AGI) with the potential capacity for human-like general problem-solving ability, as well as a model for a General Collective Intelligence or GCI, which has been described as software that organizes a group into a single collective intelligence with the potential for vastly greater general problem-solving ability than any individual in the group. Both this model for GCI and this model for AGI require functional modeling of concepts that is complete in terms of meaning being self-contained in the model and not requiring interpretation based on information outside the model. This definition of a model for cognition has also been suggested to implicitly provide a semantic interpretation of functional models created within the functional modeling technique defined to meet the data format requirements of this AGI and GCI, so that the combination of the model of cognition to define an interpretation of meaning, and the functional modeling technique, together result in fully self-contained definitions of meaning that are suggested to be the first complete implementation of semantic modeling. With this semantic modeling, and with these models for AGI and GCI, cognitive computing is far better defined. This paper explores the various computing methods and advanced computing paradigms from the perspective of this cognitive computing.

The Teaching of General Problem Solving Strategies

1986 ◽  
Vol 4 (2) ◽  
pp. 85-88 ◽  
Author(s):  
Harvey B. Adams
Keyword(s):  
Problem Solving ◽  
General Problem ◽  
General Model ◽  
Problem Solving Strategies ◽  
The Subject ◽  
Problem Solving Process ◽  
Definition Of

In this article the author advocates the development of problem solving ability as a fundamental aim of all teachers, regardless of the age of the pupils or the subject being taught. A definition of ‘a problem’ and a breakdown of the problem solving process is offered. This is followed by a series of guidelines for the teaching of general problem solving strategies. Finally, an illustration is given of how a general model can be taught to young (6–8 year old) children.

scholarly journals Bridging the Left - Right Political Divide with Artificial Intelligence and Collective Intelligence

2020 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Problem Solving ◽  
General Problem ◽  
Cognitive Bias ◽  
Intelligent Agents ◽  
Collective Intelligence ◽  
Optimal Solution ◽  
Functional Modeling ◽  
Political Debate ◽  
The Individual ◽  
Political Divide

A model of cognition suggests that the left vs right political debate is unsolvable. However the same model also suggests that a form of collective cognition (General Collective Intelligence or GCI) can allow education, health care, or other government services to be customized to the individual, so that individuals can choose services anywhere along the spectrum from socialized services if they desire, or private services if they desire, thereby removing any political stalemate where it might prevent any progress. Whatever services groups of individuals choose, GCI can significantly increase the quality of outcomes achievable through either socialized or private services today, in part through using information regarding the fitness of any services deployed, to improve the fitness of all services that might be deployed. The emerging field of General Collective Intelligence (GCI) explores how platforms might increase the general problem-solving ability (intelligence) of groups so that it is significantly higher than that of any individual. Where Collective Intelligence (CI) must find the optimal solution to a problem or group of problems, having general problem-solving ability, a GCI must also have the capacity to find the optimal problem to solve. In the case of political discussions, GCI must have the ability to re-frame political discourse from being focused on questions that have not proved resolvable, such as whether or not left leaning or right leaning political opinions are in general more “right” or “wrong”. Instead GCI must have the ability to refocus discussions, including on how to objectively determine whether a left or right bias optimizes outcomes in a specific context, and why. This paper explores the conjecture that determining whether a left leaning or right leaning cognitive bias is "optimal" (i.e. "true) based on any CI or other aggregate of individual reasoning that is not GCI, cannot reliably converge on "truth" because each individual cognitive bias leads to evaluating truth according to different reasoning types (type 1 or type 2) that might give conflicting answers to the same problem. However, through using functional modeling to create the capacity to represent all possible reasoning processes, and through using functional modeling to represent the domains in conceptual space in which each reasoning process is optimal, it is possible to systematically categorize an unlimited number of collective reasoning processes and the contexts in which execution of those reasoning processes with a right leaning or left leaning bias is optimal for the group. By designing GCI algorithms to incorporate each bias in its optimal context, a GCI can allow individuals to participate in collective reasoning despite their biases, while collective reasoning might still converge on "truth" in terms of functioning to optimize collective outcomes. And by deploying intelligent agents incorporating some subset of AGI to interact on the individual's behalf at significantly higher speed and scale, collective reasoning might gain the capacity to consider all reasoning and all "facts" available to any individual in the group, in order to converge on that truth while significantly increasing outcomes.

scholarly journals General Problem-Solving Ability in Natural Systems as a Model for Solving Problems from Sustainable and Self-Financing Development in Africa to Artificial General Intelligence

2021 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Sustainable Development ◽  
Problem Solving ◽  
General Problem ◽  
Tree Seedlings ◽  
General Intelligence ◽  
The Sustainable Development ◽  
Natural Systems ◽  
Artificial General Intelligence ◽  
Single Leaf ◽  
Wide Range

Natural systems have demonstrated the ability to solve a wide range of adaptive problems as well as the ability to self-assemble in a self-sustaining way that enables them to exponentially increase impact on outcomes related to those problems. In the case of photosynthesis nature solved the problem of harnessing the energy in sunlight and then leveraged self-assembling and self-sustaining processes so that exponentially increasing impact on that problem is reliably achievable. Rather than having to budget a given amount of resources to create a mature tree, where those resources might not be reliably available, tree seedlings self-assemble in a self-sustaining way from very few resources to grow from having the capability of photosynthesis accompanying a single leaf, to the capability of photosynthesis accompanying what might be millions of leaves. If the patterns underlying this adaptive problem-solving could be abstracted so that they are generally applicable, they might be applied to social and other problems occurring at scales that currently are not reliably solvable. One is the Sustainable Development Goals (SDGs) funding gap. The funding believed to be required to address the SDGs is difficult to estimate, and may be anywhere between $2 trillion and $6 trillion USD per year. However, bridging the gap between the funding required to meet these goals and the funding available to do so is universally acknowledged to be a difficult and unsolved problem. This paper explores how abstracting the pattern for general problem-solving ability that nature has used to solve the problem of exponentially increasing impact on collective problems, and that nature has proven to be effective for billions of years, might be reused to solve “wicked problems” from implementing an Artificial General Intelligence (AGI) to funding sustainable development at the scale required to transform Africa and the world.

Learning Through Business Games

2008 ◽  
Vol 40 (1) ◽  
pp. 68-83 ◽  
Author(s):  
Richard Fortmüller
Keyword(s):  
Problem Solving ◽  
General Problem ◽  
Cognitive Learning ◽  
Learning Processes ◽  
Learning Objectives ◽  
Learning Theories ◽  
Learning Conditions ◽  
Problem Solving Strategies ◽  
Points Of View ◽  
Definition Of

The didactic function of business games is often seen only in the development of sociocommunicative competences and general problem-solving strategies. An equally important aspect of business games lies in the acquirement of technical and problem-oriented knowledge, which is the focus of this article. Moreover, this knowledge dimension is further elaborated and justified based on four areas of learning objectives seen from learning—theoretical and from didactic points of view: (a) the definition of these structures of knowledge that (cognitive—psychologically seen) correspond to the respective areas of the learning objective; (b) referring to cognitive learning theories, the degree to which knowledge can be acquired, through which learning processes will be assessed; and (c) which conditions are suitable to trigger the respective learning processes. Didactic analyses based on these assumptions deal with the question of how these learning conditions can be implemented in business games.

scholarly journals Participatory Evaluation of Water Management Options for Climate Change Adaptation in River Basins

Environments ◽  
2021 ◽  
Vol 8 (9) ◽  
pp. 93
Author(s):  
Anabel Sanchez-Plaza ◽  
Annelies Broekman ◽  
Javier Retana ◽  
Adriana Bruggeman ◽  
Elias Giannakis ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Management ◽  
Impact Analysis ◽  
River Basins ◽  
Participatory Evaluation ◽  
Management Options ◽  
Wide Range ◽  
Definition Of ◽  
Induced Changes ◽  
The Impact

Climate and other human-induced changes will increase water scarcity in world areas such as in the Mediterranean. Adaptation principles need to be urgently incorporated into water management and stakeholder engagement needs to be strengthened at all steps of the management cycle. This study aimed to analyse and compare stakeholder-preferred water management options (WMOs) to face climate change related challenges and to foster adaptation in four Mediterranean river basins. The challenges and WMOs of the four river basins identified by stakeholders were analysed examining to what extent the WMOs tackled the identified challenges. The impact of the WMOs resulting from a participatory modelling method was included in a comparative analysis of the stakeholders’ WMOs preferences. The results indicate the participatory approach that was applied allowed local priorities and real-world challenges to be defined with adequate detail as well as the definition of tailored responses. The participatory impact analysis provided an integrated view of the river basin as an interrelated system. The participatory evaluation of the WMOs was able to consider a wide range of elements and was able reflect the combined preferences of the stakeholders. Moreover, it allowed groups of basin actors with highly diverse profiles and concerns to further promote sets of these WMOs as input into decision making processes.

Exploring the Use of Functional Models in Biomimetic Conceptual Design

2008 ◽  
Vol 130 (12) ◽  
Author(s):  
Robert L. Nagel ◽  
Prem A. Midha ◽  
Andrea Tinsley ◽  
Robert B. Stone ◽  
Daniel A. McAdams ◽  
...  
Keyword(s):  
Problem Solving ◽  
Case Studies ◽  
Biological System ◽  
Biological Systems ◽  
Flapping Wing ◽  
Functional Modeling ◽  
Functional Models ◽  
Biological World ◽  
Many Sources ◽  
High Level

The biological world provides numerous cases for analogy and inspiration. From simple cases such as hook and latch attachments to articulated-wing flying vehicles, nature provides many sources for ideas. Though biological systems provide a wealth of elegant and ingenious approaches to problem solving, there are challenges that prevent designers from leveraging the full insight of the biological world into the designed world. This paper describes how those challenges can be overcome through functional analogy. Through the creation of a function-based repository, designers can find biomimetic solutions by searching the function for which a solution is needed. A biomimetic function-based repository enables learning, practicing, and researching designers to fully leverage the elegance and insight of the biological world. In this paper, we present the initial efforts of functional modeling biological systems and then transferring the principles of the biological system to an engineered system. Four case studies are presented in this paper. These case studies include a biological solution to a problem found in nature and engineered solutions corresponding to the high-level functionality of the biological solution, i.e., a housefly’s winged flight and a flapping wing aircraft. The case studies show that unique creative engineered solutions can be generated through functional analogy with nature.

scholarly journals Prevention and protection technologies – How do the growers get ready for climate change?

2011 ◽  
Vol 17 (4-5) ◽  
Author(s):  
D. D. Nagyné ◽  
Z. Szabó ◽  
J. Nyéki ◽  
M. Soltész
Keyword(s):  
Climate Change ◽  
Extreme Weather Events ◽  
Ongoing Research ◽  
Weather Events ◽  
Wide Range ◽  
Realistic View ◽  
Fruit Growing ◽  
Unfavourable Weather ◽  
Definition Of ◽  
Technical Solutions

Within the sector of fruit growing, climate change related tasks cover a rather wide range of activities. According to what is claimed by the literature, all decisions impacting the sector should be made conformably with climate change in order to advance an increase in yield security. This, regardless of the impacts of climate change, is also one of the key questions in fruit growing. Regarding protection against extreme weather events, in addition to technological and technical elements, the level of importance assumed by farmers for the abovementioned protection techniques as well as the type and extent they intend to use of this in practice are also worth of studying. This ongoing research beginning in 2009 mainly focuses on studying the opinions of fruit farmers making up the target group for this analysis. The questionnaire survey primarily intends to study their knowledge on the definition of climate change as reactivity to unfavourable weather events occurring in the growing. The study aims at providing a realistic view on the fruit-farmers’ knowledge on climate change and on how technological elements, new technical solutions applicable to mitigate damage are used during production.

Sign in / Sign up

Export Citation Format

Share Document