A bare bones bacterial foraging optimization algorithm

Bacterial foraging optimization (BFO), based on the social foraging behaviors of bacteria, is a new intelligent optimizer. It has been widely accepted as an optimization algorithm of current interest for a variety of fields. However, compared with other optimizers, the BFO possesses a poor convergence performance over complex optimization problems. To improve the optimization capability of the BFO, in this paper a bare bones bacterial foraging optimization (BBBFO) algorithm is developed. First, a chemotactic strategy based on Gaussian distribution is incorporated into this method through making use of both the historical information of individual and the share information of group. Then the swarm diversity is introduced in the reproduction strategy to promote the exploration ability of the algorithm. The performance of BBBFO is verified on various benchmark functions, the comparative results reveal that the proposed approach is more superior to its counterparts.     

Beyond design: cybernetics,biological computers and hylozoism

The history of British cybernetics offers us a different form of science and engineering, one that does not seek to dominate nature through knowledge. I want to say that one can distinguish two different paradigms in the history of science and technology: the one that Heidegger despised, which we could call the Modern paradigm, and another, cybernetic, nonModern, paradigm that he might have approved of. This essay focusses on work in the 1950s and early 1960s by two of Britain’s leading cyberneticians, Stafford Beer and Gordon Pask, in the field of what one can call biological computing. My object is to get as clear as I can on what Beer and Pask were up to. At the end, I will discuss Beer’s hylozoist ontology of matter, mind and spirit. This material is not easy to get the hang of—but that is what one should expect from an unfamiliar paradigm. Presented at an international conference on the philosophy of technology, Copenhagen, 13–15 Oct 2005. Revised for submission to Synthese.     

Empirical and modeling study of emotional state dynamics in social videogame paradigms

The objective of this work was to study the dynamics of human emotional states in the process of social interaction in a virtual environment. The previously developed for this purpose prototypes of the virtual actor (NPC) and its virtual environment simulator “Teleport” underwent significant re-design and modification. The experimental platform was re-implemented and used in experiments with college student participants, combining electromyography, emotion recognition in facial recordings and model-based game log analysis in a social videogame paradigm. Participants interacted with two virtual actors implemented based on the eBICA cognitive architecture (Samsonovich, 2013, 2018). Positive correlations were found between eBICA model predictions and participant affects extracted from their facial expressions and facial muscle activity. Affective dynamics of social phenomena, such as the establishment of partnership or an act of betrayal, were characterized and found consistent with the model predictions. Other findings include a gradually developing emotional reaction, possibly due to the integration of appraisals of game events. Overall, obtained results confirm the eBICA model, suggesting its further extension and refinement.     

Ethical Calibration for an Intelligent Analysis Society

With the widespread application of data-driven intelligent technologies, data is increasingly used to record and influence the behavior of the world and people. Although the value rationality of dataism behind the dataization of the world has yet to be thoroughly analyzed, the new data analysis society which is characterized by an intelligent social form has quietly arrived. From a phenomenological point of view, the foundation of the operation and governance of a data analysis society is to analyze human behavior by using data and intelligent algorithms, but this kind of intelligent surveillance is speculative cognition, which may misread and improperly interfere with the agency of observed. There is an urgent need to set boundaries for possible technological abuse. At the same time, in view of the fact that data-driven social computing attempts to influence human behavior through the calculation of human behavior, the value of human behavior itself should be questioned as a problem to be solved. Further, in the face of the potential challenges of machine cognition and engineering thinking to human nature in the construction of an intelligent society, it is urgent to construct an ethical reflection arc that can restrict and correct its abuse.     

浅谈情绪智力与人工智能中的感情计算

基于情绪智力是加工、处理情绪及情绪信息的能力,而人工智能中的感情计算是要赋予计算机与人互动过程中情感信息的加工能力,人脑处理情绪信息的能力与电脑处理情绪信息的能力可以进行类比。近几年来,人工智能专家已经认识到情绪智力在感情计算中的重要作用和意义,把人类识别和表达情感的能力赋予计算机,开发了具有部分感情能力的计算机。新一代感情计算机的研发和应用依赖于人工智能专家与心理学家之间的密切合作,两者的研究成果可以相互借鉴和互补     

IN ALGORITHMS WE TRUST: MAGICAL THINKING,SUPERINTELLIGENT AI AND QUANTUM COMPUTING

This article analyzes current attitudes toward artificial intelligence (AI) and quantum computing and argues that they represent a modern-day form of magical thinking. It proposes that AI and quantum computing are thus excellent examples of the ways that traditional distinctions between religion, science, and magic fail to account for the vibrancy and energy that surround modern technologies.     

Organisms,machines, and societies: From the vertical structure of adaptability to the management of information

The adaptability of organisms and human societies depends on the synergistic orchestration of processing modes at many different levels of organization, each with unique informational characteristics. Digital information technology is a narrow transect of this spectrum. Adaptability theory provides a tool for analyzing the interactions between these fundamentally different modes of processing and for delineating the factors that can lead to either positive or negative consequences for human life.     

Learning in LIDA

LIDA is a systems-level, biologically-inspired cognitive architecture. More than a decade of research on LIDA has seen much conceptual work on its learning mechanisms, and resulted in a set of conceptual commitments that constrain those mechanisms; perhaps the most essential of these constraints is the Conscious Learning Hypothesis from Global Workspace Theory, which asserts that all significant learning requires consciousness. Despite these successes, many conceptual challenges remain, and bridging the divide between LIDA’s conceptual model and its implementations has been challenging.The contributions of this paper are threefold: We present a detailed survey of learning in LIDA, during which we clarify, elaborate on, and synthesize together ideas from numerous papers, using updated terminology that reflects the continuing evolution of LIDA. We explore foundational issues in learning, such as, “What must be innate or built-in?” versus “What can be learned?”, the nature of LIDA’s representations, and the relationship between the LIDA conceptual model and its computational realizations. Finally, we provide a roadmap for future work. We believe that this paper will direct and catalyze our research endeavors, and provide a thorough introduction to the conceptual foundations of LIDA’s learning mechanisms that will be useful to anyone that would like a deeper understanding of LIDA or for those that plan to implement LIDA-based agents.     

基于情绪认知评价理论的虚拟人情绪模型研究

情感计算是人工智能的前沿领域之一,建立具有情绪表现力的人机智能系统具有广泛的社会需求。本文分析了基于情绪认知评价理论的情绪建模方法,总结了典型的虚拟人情绪计算模型,归纳了情绪和感知的相关成果,梳理了虚拟人情绪表现方法。针对情绪建模所要深入研究的问题,分析现有研究中存在的不足,对虚拟人情绪模型研究的未来发展方向提出了建议,为进一步深入研究虚拟人情绪模型提供了参考。     

Are You Alive? Sensor Data as a Resource for Social Interaction

This paper presents findings from the field test of a prototype device that collects heart rate sensor data and displays it for users. The prototype was tested on a football team, including teenage players, their parents and coaches. The findings include notes on user expectations related to the technology and detailed analyses of the social interactions that took place during the test. The paper concludes with design implications relating to this application, but also poses challenges for context-aware computing and machine intelligence in general.