The study of multi-agent systems (MAS) focuses on systems in which many intelligent agents interact with each other. These agents are considered to be autonomous entities such as software programs or robots. Their interactions can either be cooperative (for example as in an ant colony) or selfish (as in a free market economy). This book assumes only basic knowledge of algorithms and discrete maths, both of which are taught as standard in the first or second year of computer science degree programmes. A basic knowledge of artificial intelligence would useful to help understand some of the issues, but is not essential. The books main aims are: To introduce the student to the concept of agents and multi-agent systems, and the main applications for which they are appropriate To introduce the main issues surrounding the design of intelligent agents To introduce the main issues surrounding the design of a multi-agent society To introduce a number of typical applications for agent technology

An Introduction to MultiAgent Systems.

We have used 199 million papers over 5 decades and 21 million patents to demonstrate that teams increasingly dominate solo authors in the production of knowledge Research is increasingly done in teams across nearly all fields Teams typically produce more frequently cited research than individuals do, and this advantage has been increasing over time Teams now also produce the exceptionally high-impact research, even where that distinction was once the domain of solo authors These results are detailed for sciences and engineering, social sciences, arts and humanities, and patents, suggesting that the process of knowledge creation has fundamentally changed

/pdf/the-increasing-dominance-of-teams-in-production-of-knowledge-h591ohwfzk.pdf

The Increasing Dominance of Teams in Production of Knowledge

Anti-Oedipus: Capitalism and schizophrenia.

Gesture recognition for human-robot collaboration: A review

The experience of simultaneously positive and negative orientations toward a person, goal, task, idea, and such appears to be quite common in organizations, but it is poorly understood. We develop a multilevel perspective on ambivalence in organizations that demonstrates how this phenomenon is integral to certain cognitive and emotional processes and important outcomes. Specifically, we discuss the organizational triggers of ambivalence and the cognitive and emotional mechanisms through which ambivalence diffuses between the individual and collective levels of analysis. We offer an integrative framework of major responses to highly intense ambivalence avoidance, domination, compromise, and holism that is applicable to actors at the individual and collective levels. The positive and negative outcomes associated with each response, and the conditions under which each is most effective, are explored. Although ambivalence is uncomfortable for actors, it has the potential to foster growth in the actor as well as highly adaptive and effective behavior.

/pdf/ambivalence-in-organizations-a-multilevel-approach-2t0d2fl2wy.pdf

Ambivalence in Organizations: A Multilevel Approach

Deakin Motion Lab presents The Crack Up, a transmedia production choreographed by Kim Vincs. Live dancers and virtual performers are set against 3D projected landscapes. Audience members wear 3D glasses and become fully immersed in an environment inspired by F. Scott Fitzgerald's 1936 short story 'The Crack Up', a loose-form story of a man losing his grip on reality. The signature interactive device The Crack Up App enhances the experience of live performance along with hi-definition virtual landscapes. The Crack Up showcases the outcomes of a three-year, Australian Research Council Discovery research project at Deakin Motion.Lab in motion capture, stereoscopic projection, augmented reality and interactive digital systems that have developed new ways to integrate these technologies within live performance. The Crack Up plays on these ideas of reality and transports the viewer to a world where the virtual and physical intertwine. This augmented reality lets the viewer choose their own journey and challenges the perceptions of what is dance performance. ​

The crack up

There are exceptions. If a rocket has thrust that is greater than its weight, it will accelerate away from the Earth. Another exception is a rocket or any object coasting away from the Earth, with enough speed, so that it never returns. Escape velocity is the minimum velocity an object in free-fall can have and still not be pulled back to Earth. We can determine the escape velocity of an object leaving any planet or star by using the principle of conservation of energy. Letʼs use conservation of energy to calculate the escape velocity of a projectile leaving the Earth.

Escape velocity

The repetitive and forceful motions used by operating surgeons increase the risk of developing musculoskeletal disorders. Most ergonomists consider the surgical environment to be incredibly harsh for its workers. Traditional Laparoscopic Surgery (TLS) in particular has a number of physical and mental challenges associated with it, and while Robotic-Assisted Laparoscopic Surgery (RALS) provides several features that improve upon TLS, some surgeons have still reported musculoskeletal symptoms they attribute to RALS. In this paper, we endeavored to systematically review muscle activation for both TLS and RALS, to compare the modalities and present the results as a meta-analysis. A literature search was conducted using Pubmed, Embase, and Cochrane databases in November 2018 with the following inclusion criteria: full text was available in English, the paper contained original data, EMG was one of the primary measurement techniques, and the paper included EMG data for both TLS and RALS. Results from studies were compared using standardized mean difference analysis. A total of 379 papers were found, and through screening ten were selected for inclusion. Sample populations ranged from 1 to 31 surgeons, and a variety of study designs and metrics were used between studies. The biceps were the only muscle group that consistently and significantly demonstrated lower muscle activation for RALS for all included studies. The results may support the belief that RALS is ergonomically superior to TLS, shown through generally lower muscle activation scores. However, these results must be interpreted with caution due to the heterogeneity between the studies and multiple potential sources for bias within studies. This analysis would be strengthened with a higher number of homogenous, high-quality studies examining larger sample sizes.

Muscle activation during traditional laparoscopic surgery compared with robot-assisted laparoscopic surgery: a meta-analysis

For a Digital Performing Agent to be able to perform live with a human dancer, it would be useful for the agent to be able to contextualize the movement the dancer is performing and to have a suitable movement vocabulary with which to contribute to the performance. In this paper we will discuss our research into the use of Artificial Neural Networks (ANN) as a means of allowing a software agent to learn a shared vocabulary of movement from a dancer. The agent is able to use the learnt movements to form an internal representation of what the dancer is performing, allowing it to follow the dancer, generate movement sequences based on the dancer's current movement and dance independently of the dancer using a shared movement vocabulary. By combining the ANN with a Hidden Markov Model (HMM) the agent is able to recognize short full body movement phrases and respond when the dancer performs these phrases. We consider the relationship between the dancer and agent as a means of supporting the agent's learning and performance, rather than developing the agent's capability in a self-contained fashion.

Teaching a Digital Performing Agent: Artificial Neural Network and Hidden Markov Model for recognising and performing dance movement

Artificial neural networks are an effective means of allowing software agents to learn about and filter aspects of their domain In this paper we explore the use of artificial neural networks in the context of dance performance The software agent’s neural network is presented with movement in the form of motion capture streams, both pre-recorded and live Learning can be viewed as analogous to rehearsal, recognition and response to performance The interrelationship between the software agent and dancer throughout the process is considered as a potential means of allowing the agent to function beyond its limited self-contained capability

Learning to dance with a human

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