Rahwan et al. 2019 called for a new field 'machine behavior' in which best explanations of machines combine holistic methods from ethology, social sciences, and cognitive science.

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• Rahwan et al. 2019 Machine Behaviour (Nature)concept0.861
  The landmark paper calling for the field of machine behavior; the present paper extends its framework
• Progress in machine behavior science and biohybrid engineering breaks down the simplistic dualism of life vs. machine, revealing a continuum of emergence, rational control, and agency.claim0.818
  Second central claim: life and machine form a continuous multidimensional space, not discrete bins
• Modern machines are increasingly resistant to reductionist analysis and explanation.claim0.807
  Deep neural networks, swarms, and complex autonomous systems require holistic ethological and cognitive approaches.
• Progress in theory and practice requires a novel conception of 'machines as they could be,' based on the profound lessons of biology at all scales.claim0.798
  The paper's overarching constructive goal, paralleling Langton's 'life as it could be'
• Late-20th-century holistic science still describes mechanisms; it has not overcome the mechanistic character of its models.claim0.789
  Even the beautiful descriptions of wholeness by scientists like Mae-Wan Ho remain mechanistic in detail and have not solved the bifurcation.
• Current research examines distributed cognition and AI consciousness separately rather than as integrated phenomena where machine consciousness emerges from inter-agent cognitive processes.claim0.778
  Main interpretive assertion of the search result; identifies the gap between existing literature domains and the novel research direction.
• Conceptual advances in the links between machine learning and evolution now provide quantitative formalisms with which to begin to develop testable models of collective intelligence across scales.claim0.777
  Asserts that the time is ripe for formal models.
• Future work should develop fully-fledged dynamic theories combining qualitative and quantitative information in the style of Game Semantics and Geometry of Interaction.hypothesis0.776
  Paper identifies major research objective: extending static reconciliations (Domain Theory + Shannon) to dynamic frameworks.