Paper Citation Record · LEDGER

Creating Hierarchical Dispositions of Needs in an Agent

As of 13 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2412.00044.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.00044 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:17:56.716371Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

19 of 19 outbound references displayed

verified exact1
verified fuzzy7
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 893327a0-daa9-4ced-8f96-6c6b4decf7f8 · outbound

This paper cites Human-level control through deep reinforcement learning,.

Creating Hierarchical Dispositions of Needs in an Agent Human-level control through deep reinforcement learning,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T14:17:56.615802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 006f0075-bde4-4039-9815-e3192dca0299 · outbound

This paper cites Mastering the game of go without human knowledge,.

Creating Hierarchical Dispositions of Needs in an Agent Mastering the game of go without human knowledge,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T14:17:56.621621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dad54566-7e22-4fa5-b4b8-a32e383fa42f · outbound

This paper cites Deep learning,.

Creating Hierarchical Dispositions of Needs in an Agent Deep learning,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T14:17:56.627220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcbd914d-0847-4bab-a406-3e38d4976e9e · outbound

This paper cites Trust region policy optimization,.

Creating Hierarchical Dispositions of Needs in an Agent Trust region policy optimization,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T14:17:56.632608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e5d5c0f-b1c0-4ffa-ac7d-f18b16b29384 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Creating Hierarchical Dispositions of Needs in an Agent Proximal Policy Optimization Algorithms

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T14:17:56.639032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42061727-31ff-4bef-ae7b-598af38bea79 · outbound

This paper cites Asynchronous methods for deep reinforce- ment learning,.

Creating Hierarchical Dispositions of Needs in an Agent Asynchronous methods for deep reinforce- ment learning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:57.007925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7b0a7a53-2322-435c-9f34-f60a3ad10df3 · outbound

This paper cites Sample Efficient Actor-Critic with Experience Replay.

Creating Hierarchical Dispositions of Needs in an Agent Sample Efficient Actor-Critic with Experience Replay

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T14:17:56.650828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4708bda2-229f-4729-b34c-86a5dff93d83 · outbound

This paper cites Improving stochastic policy gradients in continuous control with deep reinforcement learning using the beta distribution,.

Creating Hierarchical Dispositions of Needs in an Agent Improving stochastic policy gradients in continuous control with deep reinforcement learning using the beta distribution,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:56.989685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation acb1e5f1-ed2c-41b3-adb8-8a3e06f7730d · outbound

This paper cites Policy gradient methods for Reinforcement learning with function approxima- Tion,.

Creating Hierarchical Dispositions of Needs in an Agent Policy gradient methods for Reinforcement learning with function approxima- Tion,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:56.971766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b225557f-a15a-4c57-91bf-37e37bb8a09a · outbound

This paper cites High-Dimensional Continuous Control Using Generalized Advantage Estimation.

Creating Hierarchical Dispositions of Needs in an Agent High-Dimensional Continuous Control Using Generalized Advantage Estimation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T14:17:56.668545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1432fe3-bd89-44fc-8d89-3741525db322 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Creating Hierarchical Dispositions of Needs in an Agent Adam: A Method for Stochastic Optimization

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T14:17:56.673848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b7b6272-e08b-4c67-a6a4-9cfd876f7309 · outbound

This paper cites Openai gym,.

Creating Hierarchical Dispositions of Needs in an Agent Openai gym,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T14:17:56.679031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf880f91-51a8-497a-af10-7e338259fe35 · outbound

This paper cites Pytorch implementations of reinforcement learning algo- rithms,.

Creating Hierarchical Dispositions of Needs in an Agent Pytorch implementations of reinforcement learning algo- rithms,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:56.942830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7829f68e-9339-4baa-99d1-3b686657cd0f · outbound

This paper cites Recurrent world models facilitate policy evolution,.

Creating Hierarchical Dispositions of Needs in an Agent Recurrent world models facilitate policy evolution,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:56.925230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 424f05f9-f264-4d69-a2ca-e834592b8143 · outbound

This paper cites Optimizing agent training with deep learning on a self-driving reinforcement learning environment,.

Creating Hierarchical Dispositions of Needs in an Agent Optimizing agent training with deep learning on a self-driving reinforcement learning environment,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:56.908561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f66fac9e-d7e7-4bfe-98de-71296c15edca · outbound

This paper cites Deep neuroevolution of recurrent and discrete world models,.

Creating Hierarchical Dispositions of Needs in an Agent Deep neuroevolution of recurrent and discrete world models,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:17:56.891537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b438aaa7-ffe4-4bf8-90b5-170587b97907 · outbound

This paper cites Weight Agnostic Neural Networks.

Creating Hierarchical Dispositions of Needs in an Agent Weight Agnostic Neural Networks

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T14:17:56.705120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d94341fd-68cf-4e37-b170-59a4cebc06d4 · outbound

This paper cites Augmenting GAIL with BC for sample efficient imitation learning.

Creating Hierarchical Dispositions of Needs in an Agent Augmenting GAIL with BC for sample efficient imitation learning

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-12T14:17:56.767474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8d309a66-612b-4d40-b54f-a8449bada93a · outbound

This paper cites an unresolved cited work.

Creating Hierarchical Dispositions of Needs in an Agent Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-12T14:17:56.873637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.