Recently, I immersed myself in researching the possibility of a general formal definition of "agency".
More specifically, I’m interested in formalizations that could support an operational definition of agency across domains. I’m looking for something that captures what is common between entities that intuitively seem agentic to us in very different parts of the world, and that could, at least in principle, let us detect such entities automatically in real systems.
So far, many definitions of agency I’ve seen quickly rely on terms like “goal”, “intention”, “belief”, “choice”, “sensor”, “actuator”, and so on. These can be useful in a particular context, but they are less satisfying if I want to take an arbitrary dynamical system and ask: “is there anything agent-like here, and can we detect it without hand-labeling the agent in advance?”
So my short request is: if you know good papers that formalize agency, or important aspects of agency, at a fairly general level? I’d be very grateful for pointers.
As a starting point, I’ve been thinking within the embedded agency framing. So far, I have found two papers that seem very valuable because they formalize some “component parts” of agency.
The first one is “Semantic information, autonomous agency, and nonequilibrium statistical physics” (2018). What I found useful there is the idea that, for many agents, maintaining viability is an implicit instrumental requirement, regardless of the particular utility function we might later ascribe to them. And that we can use this feature to detect systems via their information content, because, to sustain itself, a system should use its internal information about the environment. This paper attempts to formalize the calculation of such information that a system has about the environment, in a statistical sense, and to detect the part of that information that is causally necessary for the system to maintain its existence over time — “semantic information”, in the authors’ terminology.
The authors describe a way to formalize both the amount of such information and the part of it that is actually necessary for viability. I especially liked their suggestion that this could lead to an automatic detector of agents: roughly, by searching for system/environment decompositions in which the “system” contains a high concentration of semantic information relevant to its own viability.
They propose looking at so-called "integrated spatiotemporal patterns" — roughly, statistically integrated structures extended across space and time — and they try to formalize this in the setting of dynamic Bayesian networks. I found this interesting as an attempt to define “the same object” through its organization over time, rather than through the persistence of particular material parts. This gave me the intuition that, when looking for agents, it may be better to search for system boundaries by tracking a certain kind of specified/integrated information as it moves through different physical elements of the environment.
My current plan is to follow the citation graph around these papers, both forward and backward. But I’d be very grateful for recommendations that may lie outside that graph. I suspect many people here know this literature much better than I do.
I’m especially interested in work that tries to automatically find or track “agent-like” structures inside a world, and in papers that test such ideas in concrete environments: toy simulations, cellular automata, artificial life systems, game-like worlds, and so on.
Purely philosophical overviews without a formalism are probably less useful for my current purpose, in which an agent is already assumed to be an entity that has "observations", "actions", and "rewards", but these terms are not further reduced to something you can figure out how to compute. Such work can still be useful conceptually, but right now I’m mainly looking for mathematical tools for the question: “what makes a system agentic?”
If you know a paper, author, keyword, research direction, or even just “look at the bibliography around X”, I’d really appreciate it. It would be especially helpful if you could briefly say why the work is relevant — for example: “formalizes the boundary of an agent”, “deals with self-maintenance”, “addresses the tracking problem”, “defines a measure of individuality”, “connects agency with information flow”, etc.
Hi!
Recently, I immersed myself in researching the possibility of a general formal definition of "agency".
More specifically, I’m interested in formalizations that could support an operational definition of agency across domains. I’m looking for something that captures what is common between entities that intuitively seem agentic to us in very different parts of the world, and that could, at least in principle, let us detect such entities automatically in real systems.
So far, many definitions of agency I’ve seen quickly rely on terms like “goal”, “intention”, “belief”, “choice”, “sensor”, “actuator”, and so on. These can be useful in a particular context, but they are less satisfying if I want to take an arbitrary dynamical system and ask: “is there anything agent-like here, and can we detect it without hand-labeling the agent in advance?”
So my short request is: if you know good papers that formalize agency, or important aspects of agency, at a fairly general level? I’d be very grateful for pointers.
As a starting point, I’ve been thinking within the embedded agency framing. So far, I have found two papers that seem very valuable because they formalize some “component parts” of agency.
The first one is “Semantic information, autonomous agency, and nonequilibrium statistical physics” (2018). What I found useful there is the idea that, for many agents, maintaining viability is an implicit instrumental requirement, regardless of the particular utility function we might later ascribe to them. And that we can use this feature to detect systems via their information content, because, to sustain itself, a system should use its internal information about the environment. This paper attempts to formalize the calculation of such information that a system has about the environment, in a statistical sense, and to detect the part of that information that is causally necessary for the system to maintain its existence over time — “semantic information”, in the authors’ terminology.
The authors describe a way to formalize both the amount of such information and the part of it that is actually necessary for viability. I especially liked their suggestion that this could lead to an automatic detector of agents: roughly, by searching for system/environment decompositions in which the “system” contains a high concentration of semantic information relevant to its own viability.
The second paper is “Towards information based spatiotemporal patterns as a foundation for agent representation in dynamical systems” (2016). The authors discuss the tracking problem: if an agent metabolizes, moves, and can appear differently across different trajectories, then, obviously, it cannot simply be identified with a fixed set of particles or a fixed region of space.
They propose looking at so-called "integrated spatiotemporal patterns" — roughly, statistically integrated structures extended across space and time — and they try to formalize this in the setting of dynamic Bayesian networks. I found this interesting as an attempt to define “the same object” through its organization over time, rather than through the persistence of particular material parts. This gave me the intuition that, when looking for agents, it may be better to search for system boundaries by tracking a certain kind of specified/integrated information as it moves through different physical elements of the environment.
My current plan is to follow the citation graph around these papers, both forward and backward. But I’d be very grateful for recommendations that may lie outside that graph. I suspect many people here know this literature much better than I do.
I’m especially interested in work that tries to automatically find or track “agent-like” structures inside a world, and in papers that test such ideas in concrete environments: toy simulations, cellular automata, artificial life systems, game-like worlds, and so on.
Purely philosophical overviews without a formalism are probably less useful for my current purpose, in which an agent is already assumed to be an entity that has "observations", "actions", and "rewards", but these terms are not further reduced to something you can figure out how to compute. Such work can still be useful conceptually, but right now I’m mainly looking for mathematical tools for the question: “what makes a system agentic?”
If you know a paper, author, keyword, research direction, or even just “look at the bibliography around X”, I’d really appreciate it. It would be especially helpful if you could briefly say why the work is relevant — for example: “formalizes the boundary of an agent”, “deals with self-maintenance”, “addresses the tracking problem”, “defines a measure of individuality”, “connects agency with information flow”, etc.
Thanks in advance!