DG A: Open Endedness with Automata Chemistries
| Facilitator: Susan Stepney | Time: Monday 13:00 - 14:30 | Room: 4A05 |
I will discuss how we can use automata chemistries in ALife research to generate computational systems that exhibit Open-Ended behaviour. First, I will describe the framework of models, metamodels, and metametamodels (it stops there!), and use it to give a precise definition of three levels of novelty: variation, innovation, and transformation. I will explain why most agent-based evolutionary systems can exhibit only variation (level 0 novelty). Second, I will define what automata chemistries are, and give some examples (Tierra, Avida, Physys, nanopond, Stringmol). I will explain how these systems exhibit open-ended innovation (level 1 novelty). Third (the research challenge) I will discuss what is needed to exhibit transformation (level 2 novelty), and how automata chemistries might be extended to implement this.
DG B: Emergence of hierarchical intelligence in simulated agents
| Facilitator: Eric Medvet | Time: Monday 13:00 - 14:30 | Room: 5A09 |
Complex tasks require the agent to act on two levels simultaneously: locally, to perform low-level behaviors and manage close environmental events; and globally, to strategize and achieve the task goal. These local and global may exist both in time or space, shaping a hierarchy in the agent intelligence. For example, while navigating an arena, a differential-drive robot might first plan a sketched trajectory (global in time) and then reactively move avoiding obstacles while attempting to follow the planned trajectory (local in time). A modular robot may govern its behavior by first dictating sketches of behavior to subsets of the modules (global in space) and then actuating the single modules based on their role in the body (local in space). In this project, we want to investigate the factors enabling and favoring the emergence of hierarchical (embodied) intelligence in simple simulated agents subjected to optimization: what are the brain/body structures which mostly favor this emergence? What are the best objectives for driving the optimization? How to detect/monitor the emergence of an hierarchy?
DG C: Why do living organisms exist?
| Facilitator: Stefano Nichele | Time: Monday 13:00 - 14:30 | Room: 3A07 |
Why do living organisms exist? This question was addressed in 1953 by Nils Barricelli, one of the founding fathers of artificial life, using numeric symbioorganisms (one dimensional cellular automata). In his CA models, reproduction and mutation were not sufficient to explain the origin of an evolutionary process (and therefore the origins of life). He proposed that the missing ingredient was symbiogenesis, the creation of a new entity out of a mutually beneficial relationship between two pre-existing entities. Barricelli’s work has not been fully appreciated, however it is still very relevant today. In this discussion group we will review Barricelli’s ideas on symbiogenesis, recent ideas, and identify future directions and open questions.
DG D: Environmental Buffering and the Constraint-Function Loop
| Facilitator: Alyssa Adams | Time: Monday 13:00 - 14:30 | Room: 4A09 |
This topic explores how agents restructure theit environment to reduce the need for internal information processing. While standard control theory treats the environment as unmodifiable, the idea of “environmental buffering” suggests that agents “offload” information processing to their surroundings by directly modifying their environment. By turning a complex environment into a set of stable physical constraints, agents shift the energy burden from internal information processing to the construction of external stability.
Some possible questions to start with:
- Does shaping an environment make agents more autonomous by freeing up resources, or less autonomous through external dependence?
- What if the upfront buffering cost is too high?
- If an environment is changing too much, constantly eroding any constructed stability, is it more efficient to evolve better sensors than to try to buffer?
- If an agent’s function depends on the constraints it created, where does the agent end and the environment begin?
| Facilitator: Ángel Goñi-Moreno | Time: Tuesday 10:30 - 12:00 | Room: 4A05 |
DG F: TBA
| Facilitator: Kyrre Glette | Time: Tuesday 10:30 - 12:00 | Room: 5A09 |
DG G: TBA
| Facilitator: Alexander Mordvintsev | Time: Tuesday 10:30 - 12:00 | Room: 3A07 |
