Multiagent Only Knowing in Dynamic Systems
Authors: V. Belle, G. Lakemeyer
JAIR 2014 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this work, we propose a first-order multiagent framework with knowledge, actions, sensing and only knowing, that is shown to inherit all the features of the single agent version. Most significantly, we prove reduction theorems by means of which reasoning about knowledge and actions in the framework simplifies to non-epistemic, non-dynamic reasoning about the initial situation. |
| Researcher Affiliation | Academia | Vaishak Belle EMAIL Dept. of Computer Science, University of Toronto, Toronto, Ontario, Canada M5S 3H5 Gerhard Lakemeyer EMAIL Dept. of Computer Science, RWTH Aachen University, 52056 Aachen, Germany |
| Pseudocode | Yes | Definition 17 Define R[α], the regression of a bounded basic formula α wrt Υ, to be the fluent formula R[ , α]. For any sequence of action names or variables σ, R[σ, α] is defined inductively: 1. R[σ, t1 = t2] = (t1 = t2) if t1 and t2 do not mention functional fluents; 2. R[σ, xα] = x R[σ, α]; 3. R[σ, α β] = R[σ, α] R[σ, β]; 4. R[σ, α] = R[σ, α]; 5. R[σ, [t]α] = R[σ t, α]; 6. R[σ, Poss(t)] = R[σ, πa t ]; 7. R[σ,G(t1, . . . , tk)] = G(t1, . . . ,Gk) for rigid predicate G; 8. R[σ, F(t1, . . . , tk)] for fluent predicate F is defined inductively on σ: (a) R[ , F(t1, . . . , tk)] = F(t1, . . . , tk); (b) R[σ t, F(t1, . . . , tk)] = R[σ, γF a x1 ... xk t t1 ... tk ]; 9. R[σ, f(t1, . . . , tk) = t ] for fluent function f is defined inductively by: (a) R[ , f(t1, . . . , tk) = t ] = (f(t1, . . . , tk) = t ); (b) R[σ t, f(t1, . . . , tk) = t ] = R[σ, y. (γ f )a t x1 ... xk t1 ... tk y = t ]. |
| Open Source Code | No | The paper does not contain any statements about making code available, nor does it provide links to code repositories or supplementary materials containing code. |
| Open Datasets | No | Example 12 Imagine two agents playing a simple card game. We imagine a deck of cards, numbered 1 through 52. Two face-down cards have been dealt, one to A and the other to B. Player i picks her card, reads the card and decides to challenge player j (j , i). When a challenge is posed, the player with the card that has the highest number wins the game. The paper defines an example domain (a simple card game) internally within the formalism, rather than using or referencing an external, publicly available dataset for experiments. |
| Dataset Splits | No | The paper does not conduct empirical experiments using datasets, therefore, there are no dataset splits discussed or provided. |
| Hardware Specification | No | The paper focuses on theoretical contributions and logical proofs, and therefore does not describe any specific hardware used for experiments. |
| Software Dependencies | No | The paper describes a formal logical framework and does not mention any software dependencies with specific version numbers for implementation. |
| Experiment Setup | No | The paper is theoretical in nature, focusing on logical frameworks and proofs, and as such, it does not detail any experimental setup, hyperparameters, or system-level training settings. |