Skip to main content

Currently Skimming:

IDR Team Summary 1: Using our understanding of cooperation in cognitive organisms to understand cooperation in organisms or entities without brains and vice versa.
Pages 11-20

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 11...
... The major transitions are the progression in complexity of life formulated by Maynard Smith and Szathmary, including genes into chromosomes, mitochondria and host cells into eukaryotes, single cells to multicellularity, and solitary to eusocial insects. Cooperation and control of conflict characterize these transitions, with some being formed of related individuals (fraternal transitions)
From page 12...
... Generally speaking the word robot may refer to both physical robots and virtual software agents. Talking to the experts in this field, it appears that there is no universal agreement on which machines/devices represent the robots; however, one has the general appreciation that robots could perform tasks including moving around, operating a mechanical limb, sensing and manipulating their environment, and exhibiting intelligent behavior.
From page 13...
... The field of artificial intelligent is a rapidly growing field and modern electronics and miniaturized mechanical actuators have allowed the robot designers to make their robots amazingly powerful and self-supporting! Key Questions What concepts from the social sciences have not had an impact yet on understanding cooperation in microbes, across major transitions, or within genomes?
From page 14...
... Selfish genetic elements, genetic conflict, and evolutionary innovation. Proceedings of the National Academy of Sciences of the United States of America 2011;108;10863-10870.
From page 15...
... Bacteria use chemical signals to coordinate unified actions; a selfish gene can promote its own transmission at the cost of other genes and its whole organism; and robots can be programmed to work together, completing tasks as a swarm. IDR Team 1 set out to identify underlying properties of interaction that transcend cognitive context, comparing and contrasting the mechanisms at play in diverse social systems.
From page 16...
... As in groups of social insects, the team said, each robot in a swarm executes one individual part of an emerging group behavior. Considering the coordinative behavior of robots allows a focus on the building blocks of any larger collective swarm action, the team agreed, which could provide the greatest insight when designing new social engagements.
From page 17...
... Beyond that, the mechanisms of coordination place constraints on how coordinated systems evolve." Constraints are essential, the team agreed, in understanding biological societies and designing robotic ones. The team also emphasized the importance of environmental factors in shaping coordinated behavior.
From page 18...
... Genetic conflict can lead to coordination at a species level -- for example, opposing maternal and paternal imprinting of growth hormone genes in lions will ultimately evolve into healthy cubs. The team felt that it would be important to incorporate a biological model of constraint and conflict when designing social robots.
From page 19...
... IDR TEAM SUMMARY 1 19 accurate, and broadly applicable analysis of social interactions, the mechanisms by which they develop and change, and the constraints that shape such processes. Ultimately, the IDR team concluded this would advance our understanding of collective behavior as a whole, as well as our ability to construct and optimize coordinated systems in the technology of the future.


This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More information on Chapter Skim is available.