Research of Virtual Emotional Human System Based on Artificial Life

2013 ◽  
Vol 325-326 ◽  
pp. 1792-1795
Author(s):  
Shan Po Nian ◽  
Lei Chen ◽  
Cai Xia Hou ◽  
Run Kun Gong ◽  
Li Peng
Keyword(s):  
Artificial Intelligence ◽  
Artificial Life ◽  
Self Organization ◽  
Human Intelligence ◽  
Human System ◽  
Model Method ◽  
Research Fields ◽  
Emotional Model ◽  
Self Adaptation

t is the task for artificial intelligence to give human intelligence to machine, such as thinking, reasoning and deciding, etc. To give life to a machine is the research fields of artificial life like evolution, generating, self-adaptation, self-organization, etc. Artificial emotion gives a machine various senses as laughing, anger, sorrow and happiness, etc. It is intolerable for artificial emotion to be separated from artificial life. So the research frame of the virtual emotional human system is represented. And the emotional model, method and technology are investigated in this paper. A simulation has been done. The results are encouraging and it will be applied into the interface between human and machine.

scholarly journals Individual & Collective Human Intelligence in Drug Design: Evaluating the Search Strategy

2020 ◽  
Author(s):  
Giovanni Cincilla ◽  
Simone Masoni ◽  
Jascha Blobel
Keyword(s):  
Artificial Intelligence ◽  
Drug Discovery ◽  
Drug Design ◽  
De Novo ◽  
Chemical Space ◽  
Human Intelligence ◽  
Computer Algorithms ◽  
De Novo Drug Design ◽  
Research Fields

In recent years, individual and collective human intelligence, defined as the knowledge, skills, reasoning and intuition of individuals and groups, have been used in combination with computer algorithms to solve complex scientific problems. Such approach was successfully used in different research fields such as: structural biology, comparative genomics, macromolecular crystallography and RNA design. Herein we describe an attempt to use a similar approach in small-molecule drug discovery, specifically to drive search strategies of de novo drug design. This is assessed with a case study that consists of a series of public experiments in which participants had to explore the huge chemical space in silico to find desired molecules (e.g. drug candidates). The objectives of this case study are: assess human intelligence in chemical space exploration problems; compare the performance of individual and collective human intelligence; and contrast human and artificial intelligence achievements in de novo drug design. To our knowledge this is the first time that human intelligence is being evaluated for such a task in drug discovery and, of similar importance, compared to the performance of artificial intelligence (e.g. machine learning, genetic algorithms), giving first insights towards their differences and uniqueness.

scholarly journals Individual & Collective Human Intelligence in Drug Design: Evaluating the Search Strategy

2020 ◽  
Author(s):  
Giovanni Cincilla ◽  
Simone Masoni ◽  
Jascha Blobel
Keyword(s):  
Artificial Intelligence ◽  
Drug Discovery ◽  
Drug Design ◽  
De Novo ◽  
Chemical Space ◽  
Human Intelligence ◽  
Computer Algorithms ◽  
De Novo Drug Design ◽  
Research Fields

In recent years, individual and collective human intelligence, defined as the knowledge, skills, reasoning and intuition of individuals and groups, have been used in combination with computer algorithms to solve complex scientific problems. Such approach was successfully used in different research fields such as: structural biology, comparative genomics, macromolecular crystallography and RNA design. Herein we describe an attempt to use a similar approach in small-molecule drug discovery, specifically to drive search strategies of de novo drug design. This is assessed with a case study that consists of a series of public experiments in which participants had to explore the huge chemical space in silico to find desired molecules (e.g. drug candidates). The objectives of this case study are: assess human intelligence in chemical space exploration problems; compare the performance of individual and collective human intelligence; and contrast human and artificial intelligence achievements in de novo drug design. To our knowledge this is the first time that human intelligence is being evaluated for such a task in drug discovery and, of similar importance, compared to the performance of artificial intelligence (e.g. machine learning, genetic algorithms), giving first insights towards their differences and uniqueness.

scholarly journals Emergentist View on Generative Narrative Cognition: Considering Principles of the Self-Organization of Mental Stories

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Taisuke Akimoto
Keyword(s):  
Artificial Intelligence ◽  
Computational Modeling ◽  
Organizational Structure ◽  
Internal Structure ◽  
Multiagent System ◽  
The Self ◽  
Self Organization ◽  
Human Intelligence ◽  
Conceptual Level ◽  
Living Objects

We consider the essence of human intelligence to be the ability to mentally (internally) construct a world in the form of stories through interactions with external environments. Understanding the principles of this mechanism is vital for realizing a human-like and autonomous artificial intelligence, but there are extremely complex problems involved. From this perspective, we propose a conceptual-level theory for the computational modeling of generative narrative cognition. Our basic idea can be described as follows: stories are representational elements forming an agent’s mental world and are also living objects that have the power of self-organization. In this study, we develop this idea by discussing the complexities of the internal structure of a story and the organizational structure of a mental world. In particular, we classify the principles of the self-organization of a mental world into five types of generative actions, i.e., connective, hierarchical, contextual, gathering, and adaptive. An integrative cognition is explained with these generative actions in the form of a distributed multiagent system of stories.

Intelligence, Artificial and Otherwise

2019 ◽  
Vol 24 (2) ◽  
pp. 241-258
Author(s):  
Paul Dumouchel
Keyword(s):  
Artificial Intelligence ◽  
Human Intelligence

The idea of artificial intelligence implies the existence of a form of intelligence that is “natural,” or at least not artificial. The problem is that intelligence, whether “natural” or “artificial,” is not well defined: it is hard to say what, exactly, is or constitutes intelligence. This difficulty makes it impossible to measure human intelligence against artificial intelligence on a unique scale. It does not, however, prevent us from comparing them; rather, it changes the sense and meaning of such comparisons. Comparing artificial intelligence with human intelligence could allow us to understand both forms better. This paper thus aims to compare and distinguish these two forms of intelligence, focusing on three issues: forms of embodiment, autonomy and judgment. Doing so, I argue, should enable us to have a better view of the promises and limitations of present-day artificial intelligence, along with its benefits and dangers and the place we should make for it in our culture and society.

scholarly journals Self-replication of a quantum artificial organism driven by single-photon pulses

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Daniel Valente
Keyword(s):  
Self Assembly ◽  
Artificial Life ◽  
Single Photon ◽  
Self Organization ◽  
Physical Systems ◽  
Self Organized ◽  
Living Organisms ◽  
A Chain ◽  
Thermodynamic Mechanism ◽  
Self Replication

AbstractImitating the transition from inanimate to living matter is a longstanding challenge. Artificial life has achieved computer programs that self-replicate, mutate, compete and evolve, but lacks self-organized hardwares akin to the self-assembly of the first living cells. Nonequilibrium thermodynamics has achieved lifelike self-organization in diverse physical systems, but has not yet met the open-ended evolution of living organisms. Here, I look for the emergence of an artificial-life code in a nonequilibrium physical system undergoing self-organization. I devise a toy model where the onset of self-replication of a quantum artificial organism (a chain of lambda systems) is owing to single-photon pulses added to a zero-temperature environment. I find that spontaneous mutations during self-replication are unavoidable in this model, due to rare but finite absorption of off-resonant photons. I also show that the replication probability is proportional to the absorbed work from the photon, thereby fulfilling a dissipative adaptation (a thermodynamic mechanism underlying lifelike self-organization). These results hint at self-replication as the scenario where dissipative adaptation (pointing towards convergence) coexists with open-ended evolution (pointing towards divergence).

scholarly journals Machine Learning in Healthcare Communication

Encyclopedia ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 220-239
Author(s):  
Sarkar Siddique ◽  
James C. L. Chow
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Cancer Therapy ◽  
Medical Imaging ◽  
Health Education ◽  
Human Intelligence ◽  
Computer Algorithms ◽  
Dialogue Management ◽  
Topical Review ◽  
Healthcare Communication

Machine learning (ML) is a study of computer algorithms for automation through experience. ML is a subset of artificial intelligence (AI) that develops computer systems, which are able to perform tasks generally having need of human intelligence. While healthcare communication is important in order to tactfully translate and disseminate information to support and educate patients and public, ML is proven applicable in healthcare with the ability for complex dialogue management and conversational flexibility. In this topical review, we will highlight how the application of ML/AI in healthcare communication is able to benefit humans. This includes chatbots for the COVID-19 health education, cancer therapy, and medical imaging.

scholarly journals Artificial Intelligence, Smart Contract and Islamic Finance

2018 ◽  
Vol 14 (2) ◽  
pp. 145 ◽  
Author(s):  
Siti Rohaya Mat Rahim ◽  
Zam Zuriyati Mohamad ◽  
Juliana Abu Bakar ◽  
Farhana Hanim Mohsin ◽  
Norhayati Md Isa
Keyword(s):  
Artificial Intelligence ◽  
Computer Code ◽  
Islamic Finance ◽  
Human Intelligence ◽  
Human Beings ◽  
Finance Industry ◽  
Smart Contract ◽  
Huge Impact ◽  
Block Chain

This study examines the two important aspect of latest technology issues in Islamic finance that related to artificial intelligence (AI) and smart contract. AI refers to the ability of machines to understand, think, and learn in a similar way to human beings, indicating the possibility of using computers to simulate human intelligence. Smart contract is a computer code running on top of a block-chain containing a set of rules under which the parties to that smart contract agree to interact with each other. The main objectives of this article are to evaluate the operations of AI and smart contract, to make comparison between the operations of AI and smart contract. This article concludes that AI and smart contract will have a huge impact in future for Islamic Finance industry.

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