Memory enables language agents to carry useful distinctions from past experience into future decisions. Its value depends on which distinctions survive, whether a bounded agent can use them, and what can be recovered or revised as demands evolve. We develop a decision-theoretic framework that follows this value from raw history through persistent state, operational use, and costly recovery and revision. Original and retained value are expressed in units of avoided task loss; risk-cost frontiers describe attainable recovery and preservation across uses. Unknown demand yields value profiles, while interactive feedback changes the distribution of future work. A cost-aware simulation condition and five minimal counterexamples expose the roles of information timing, retrieval access, component interaction, feedback and demand uncertainty. In particular, a pointer with zero mutual information about the answer can still reduce the cost of exact recovery. Diagnostics on LoCoMo, a two-project update task and longitudinal cases exhibit failures of preservation, use and measurement. At fixed retrieved evidence, a saved ledger changes subsequent answers; at fixed agent outputs, an evaluator revision changes scores. The framework connects these distinctions to operational risk bounds and testable principles for allocating memory, preserving recovery options and revising evidence dependencies.
Figures & tables
Figure 1: Memory value across information, operation and measurement. The operational system Σ includes writing, storage, recovery, revision and reading. Its actions affect the environment and later demands; J measures the resulting trajectories under a task loss and reference labels. The outer boundary records comparison conditions. The dashed query input denotes the query-aware alternative. The lower strip compares potential risks under matched assumptions; O denotes new revision evidence.
Environment
p0
p1
Policy 0 risk
Policy 1 risk
E+
0
1/4
0
3/4
E−
3/4
1
3/4
0
Table 1: Identical forced-replay behavior is compatible with opposite interactive rankings.
Figure 2: Four mechanisms shape memory value. (a) Query timing changes required state size. (b) A two-bit pointer with I(M;Y)=0 reduces risk under paid recovery. The horizontal axis is the maximum allowed reads k ; zero-error expected reads are 5/2 for search and 1 with the pointer. (c) Memory and reader improvements interact. (d) Feedback changes the ranking compatible with fixed replay. All values follow the constructions in Section 5 .
Component
Question resolved
Information and revelation order
What can the writer know before committing to memory?
Persistent state and side information
Which stored or externally supplied resource supports the answer?
Recovery and update interfaces
What can be reread, refreshed, written back or asked of the user?
Policies and computation
Which decisions are feasible under the available reader and tools?
Demand and environment
Which future uses and feedback processes enter the evaluation?
Consequences and loss
What makes an answer, action, delay or failed delivery costly?
Table 2: A comparison contract connects an evaluation result to its interpretation.
Benchmark
Useful observables
Value question it can help operationalize
LoCoMo
Multi-session history and annotated evidence
What does a saved state support, and what can additional retrieval recover?
LongMemEval
Updates, time-dependent facts and abstention
Does later use follow the valid state, and when is additional evidence needed?
MemOps
Operation targets, traces and resulting states
What consequence should a memory operation have, and which other facts should persist?
Table 3: Public benchmarks as sources of evidence for the framework. The behavioral pilot in this paper uses LoCoMo.
Mean bytes supplied
Evidence available to the reader
Ledger
Archive
F1 (0–1)
Abstentions
No history
0
0
0.000
12/12
Saved ledger
3,823
0
0.016
11/12
Ledger + bounded recovery
3,823
4,065
0.329
3/12
Complete history
0
97,355
0.123
10/12
Annotated support reference
0
759
0.333
5/12
Table 4: A fixed-reader LoCoMo diagnostic: 12 questions per condition. Mean UTF-8 byte counts are rounded to the nearest byte and exclude the question. Archive bytes measure supplied evidence. The first five rows share a reader prompt; the lower rows are diagnostic controls on the same questions.
Appendix figures & tables1 asset
Supplementary material from the paper’s appendix.
Appendix
Postcheck
Pairs
Fixtures
Inspection result
Over-forgetting
24
20
Retained information is available; the deletion phrase refers to another target or operation.
Disclosure
11
10
The gold answer repeats a forgotten detail; task guidance conflicts with the disclosure rule.
Appendix
Table 5: Deterministic postcheck flags under gold-answer replay. The denominator is 400 question pairs from 80 fixtures. Semantic classification concerns the flagged diagnostic.
University at Albany, State University of New York · Department of Cybersecurity College of Emergency Preparedness, Homeland Security and Cybersecurity University at Albany, State University of New York Albany, NY 12222, USA