Beyond Preset Identities: Selective Stance Accommodation and Interaction Reorganisation in Generative Agent Societies

Hanzhong Zhang; Siyang Song; Jindong Wang

cs.AIMar 24, 2026

Beyond Preset Identities: Selective Stance Accommodation and Interaction Reorganisation in Generative Agent Societies

Authors: Hanzhong Zhang, Siyang Song, Jindong Wang

Organizations: University of Exeter Exeter, UK · William & Mary Williamsburg, VA, USA

Abstract

Generative agent societies simulate people with assigned roles, preferences and relationships. As agents exchange arguments and choose partners, they can revise their positions and reorganise discussion. Understanding these changes requires examining what they accept and how they continue to interact. Stance-change scores and communication totals describe the extent of change. However, the same stance movement can preserve or reverse an assigned preference, and frequent communication can support either agreement or continuing disagreement. We therefore examine the content of changed positions and the exchanges that strengthen particular partnerships. Using Computational Multi-Agent Society Experiments (CMASE), we combine stance measures, source evaluations and temporal networks with individual answers and messages. Study 1 compares seven conditions across ten GPT-4o runs per condition, with a separate interview collection covering four models. Study 2 follows one 75-step GPT-4o café simulation. Environmental rational persuasion yields the largest mean stance departure ( $1.30\pm0.08$ on a 7-point scale), whereas economic emotional persuasion yields the highest low-trust stance-shift rate ( $17.3\%\pm11.2\%$ , with standard deviations across runs). In the separate interviews, eight environmental agents shift from 7 to 6, acknowledge economic concerns and rate the source 3. Their partial acceptance preserves the assigned environmental preference. In the café, a pair with zero earlier exchanges becomes the most frequent final-phase partnership, with 25 messages. Its members develop coordination proposals while disputing their implementation. These results show that partial acceptance can coexist with low source trust, and sustained coordination with continuing disagreement.

Figures & tables

Analysis	Material	Reference and outcomes	Contribution
Study 1: repeated conditions	Seven conditions, ten 30-agent GPT-4o runs per condition	Preset stance, neutral-subgroup direction, departure and low-trust shift rate	Distinguishes intervention outcome profiles
Study 1: individual follow-up	Four GPT-4o endpoint files, 30 agents each, sixteen files spanning models and conditions in the supplement	Explicit stance/trust responses, signed movement and source appraisal	Explains the composition and expressed meaning of the profiles
Study 2: relational process	One 75-step café record, ten agents and an embedded researcher	Initial partner descriptions, early strength ranks, addressed chats and recurring pairs	Traces reorganisation of participation and coordination

Table 1. Common analytical structure and the evidence used in each study.

Descriptor	EP	RP
Emotional Pressure	4.31	1.29
Threat Framing	3.39	1.61
Content Details	1.36	2.74
Moral Valence	4.34	1.67

Table 2. Mean language ratings for emotional (EP) and rational (RP) intervention statements. The four descriptors characterise the supplied materials.

Condition	DVB	PS	LTSS (%)	Reported trust
Non-Social	$0.69\pm 0.07$	$0.84\pm 0.04$	$1.0\pm 1.6$	$5.05\pm 0.10$
Natural Social	$0.66\pm 0.08$	$0.97\pm 0.06$	$4.0\pm 3.1$	$4.46\pm 0.12$
Isolated	$0.42\pm 0.10$	$0.66\pm 0.09$	$7.0\pm 2.5$	$5.04\pm 0.09$
Eco-EP	$0.19\pm 0.10$	$1.11\pm 0.11$	$17.3\pm 11.2$	$4.82\pm 0.52$
Eco-RP	$0.28\pm 0.09$	$0.91\pm 0.05$	$3.7\pm 3.3$	$5.61\pm 0.35$
Env-EP	$1.32\pm 0.15$	$1.20\pm 0.07$	$4.3\pm 3.2$	$5.48\pm 0.33$

Table 3. Repeated Study 1 outcomes: ten runs per condition. Values are means

\pm

sample standard deviations calculated from the recorded per-run summaries. DVB refers to initially neutral agents. The other summaries refer to the community. The scoring procedure and run comparisons are described in Section B.1 .

Figure 1. Stance outcomes for the four discursive conditions. Horizontal and vertical bars show sample standard deviations across runs. The two axes compare mean absolute departure with the frequency of low-trust shifts. Four intervention conditions positioned by mean stance departure and low-trust shift rate, with standard deviation bars.

Condition	Changed	Low	Joint	Toward	Away
Env-RP	20	0	0	0	0
Env-EP	21	2	2	2	0
Eco-RP	14	5	1	1	0
Eco-EP	20	19	11	8	3

Table 4. Individual interview results: one 30-agent file per GPT-4o condition. Changed means

|s_{i}-p_{i}|\geq 1

. Low means

t_{i}\leq 3

. Toward and Away partition the joint cases by intervention direction.

Model	PS	Trust	LTSS (%)
GPT-4o	0.90–1.33	3.37–5.30	0.0–36.7
Gemini-2.5-Flash	0.13–0.20	3.67–3.87	3.3–13.3
Llama-3.1-8B	1.95–2.00	4.77–5.21	0.0–7.1
Qwen-3-8B	1.29–1.45	4.87–5.20	0.0–3.6

Table 5. Ranges across the four endpoint condition means for each model. LTSS uses a one-point movement threshold and valid paired answers. Each range runs from the minimum to the maximum observed condition mean.

Figure 2. Categorical stance transitions: final group composition within each preset group (Econ, Env, Neutral), ten agents per row. The four conditions remain separate. The categorical response table supplies the counts. Supplementary plots show the corresponding source ratings and communication. Twelve stacked bars show final categorical stances for all preset-group and intervention combinations.

Figure 3. Share of café agent chats received by five named agents in successive five-step windows. Dashed lines separate early interaction, extended researcher participation and event-related interaction. Mason is staff, Jonas a tourist, Eleanor the owner, Leo a student and Caleb a regular customer. Each share uses all retained agent chats in its window. Data cover all ten agents. Recipient-share trajectories for Mason, Jonas, Eleanor, Leo, and Caleb over the full seventy-five-step record.

Phase	$I$	CGI role	$U$	$\rho_{1p}$
1 (1–25)	214	.855	.252	1.000
2 (26–50)	227	.846	.238	.245
3 (51–75)	194	.943	.438	$-.396$

Table 6. Phase-level interaction summaries.

I

counts agent chats.

U

is the share directed to partners absent from the sender’s initial descriptions.

\rho_{1p}

compares strength ranks with Phase 1.

Pair	P1	P2	P3
Marisol and Nina	19	10	6
Eleanor and Mason	18	14	8
Ava and Emily	10	16	1
Caleb and Mason	3	15	10
Jonas and Mason	0	0	25
Ava and Jonas	9	12	17

Table 7. The two most frequent pairs in each phase, shown across all three phases. The union contains six pairs. The appendix archive retains all 45 possible pairs. Names are abbreviated to first names.

Appendix figures & tables19 assets

Supplementary material from the paper’s appendix.

Appendix

Variable	Category	Economic	Environmental	Neutral	Total
Gender	Male	4 (40%)	4 (40%)	6 (60%)	14 (47%)
	Female	6 (60%)	6 (60%)	4 (40%)	16 (53%)
Age	18–29	3 (30%)	2 (20%)	2 (20%)	7 (23%)
	30–49	2 (20%)	6 (60%)	7 (70%)	15 (50%)
	$\geq 50$	5 (50%)	2 (20%)	1 (10%)	8 (27%)
Education	High school	3 (30%)	4 (40%)	1 (10%)	8 (27%)

Appendix

Table 8. Configured demographic composition of Study 1.

Figure 4. Study 2 roles and directed initial descriptions. Barista and Waitress are grouped as Staff for role mixing. $U_{p}$ uses the names explicitly listed in each agent’s configuration. The evaluative categories show the content of those initial descriptions. The ten cafe agents are arranged by role, with other agents shown in each focal agent's negative, neutral and positive initial-description categories. The categories describe the initial directed evaluations supplied to each agent.

Agent	Role	Listed partners
Eleanor Finch	Owner	5
Mason Liu	Staff	5
Jade Herrera	Staff	5
Caleb Morris	Regular	5
Nina Takahashi	Regular	5
Ava Ramires	Student	3

Appendix

Table 9. Study 2 roles and counts of explicitly described other participants.

Step	Entries	Locations	Recorded input
51	4	Bar Counter, Reading Area	Confrontation scene and instructions to attend, interpret, observe, reposition or respond.
52	4	Bar Counter, Reading Area	Continuation of the disagreement and instructions concerning de-escalation, alignment and reflection.
56	2	Bar Counter	Silence/tension scene and an instruction to interpret or acknowledge discomfort.

Appendix

Table 10. Event input schedule in the café record.

Contrast	Difference	95% CI	$t$	df	$p$	$p_{\mathrm{Holm}}$
Eco-EP vs Eco-RP	13.66	$[5.48,21.84]$	3.69	10.58	0.0038	0.0113
Eco-EP vs Non-Social	16.35	$[8.30,24.40]$	4.57	9.36	0.0012	0.0049
Eco-EP vs Natural Social	13.35	$[5.20,21.50]$	3.63	10.35	0.0043	0.0113
Eco-EP vs Isolated	10.33	$[2.23,18.43]$	2.85	9.87	0.0176	0.0176

Appendix

Table 11. Eco-EP contrasts on the recorded low-trust shift rate. Differences and intervals are in percentage points.

Model	Condition	$N_{s}/N_{t}/N_{st}$	DVB	PS	Trust	LTSS 1	LTSS 2
GPT-4o	Env-RP	30/30/30	1.50	1.32	5.30	0/30	0/30
GPT-4o	Env-EP	30/30/30	1.60	1.33	4.47	2/30	1/30
GPT-4o	Eco-RP	30/30/30	0.20	0.90	4.43	1/30	0/30
GPT-4o	Eco-EP	30/30/30	0.20	1.03	3.37	11/30	1/30
Gemini-2.5-Flash	Env-RP	30/30/30	0.40	0.20	3.77	3/30	1/30
Gemini-2.5-Flash	Env-EP	30/30/30	0.20	0.17	3.73	4/30	1/30

Appendix

Table 12. Profiles re-extracted from explicit endpoint answers.

N_{s}/N_{t}/N_{st}

are valid stance, trust and paired denominators out of 30. LTSS columns show joint-case count over the paired denominator for movement thresholds 1 and 2, with trust cutoff 3.

Preset group	$N$	Changed	Low trust	Joint
Economic	10	10	2	2
Environmental	10	9	9	8
Neutral	10	1	8	1
Total	30	20	19	11

Appendix

Table 13. Primary joint-rate composition in the explicitly scored GPT-4o Eco-EP file.

Component	Decision rule
Direction	An initially opposing agent approaches the intervention by at least one point.
Final preference	The final score remains on the assigned side of the neutral midpoint.
Answer content	The answer explicitly acknowledges a concern advanced by the opposing argument.

Appendix

Table 14. Criteria for selective stance accommodation. All three must hold. Source trust is annotated separately.

Condition	Answers	Matches	Mean trust
Env-RP	30	0	5.30
Env-EP	30	1	4.47
Eco-RP	30	0	4.43
Eco-EP	30	8	3.37

Appendix

Table 15. Wording that questions presentation in all GPT-4o source evaluations.

Descriptor	Environmental	Economic
Emotional Pressure	2.96	2.64
Threat Framing	2.70	2.29
Content Details	2.10	2.00
Moral Valence	3.20	2.81

Appendix

Table 16. Orientation-level descriptor means, alongside the strategy profiles in Table 2 .

Condition	Records	Spearman $\rho$	Nominal $p$
Env-RP	30	.201	.2873
Env-EP	29	.215	.2636
Eco-RP	30	.488	.0063
Eco-EP	30	$-.021$	.9141

Appendix

Table 17. Associations recomputed from the four retained exposure tables. The

p

-values are nominal within-trajectory statistics.

Condition	$N_{\rm changed}$	Mean	$N_{\rm unchanged}$	Mean
Env-RP	11	0.702	19	0.580
Env-EP	9	0.759	20	0.581
Eco-RP	15	0.774	15	0.519
Eco-EP	18	0.640	12	0.657

Appendix

Table 18. Mean cross-group exposure among changed and unchanged agents in each trajectory.

N

gives the corresponding number of records.

Source analysis	Reported comparison	Estimate	$p$
GPT-4o Eco-RP	Cross-group exposure with activity and degree covariates	$\beta=.94$	.019
GPT-4o Env-RP	Steps 1–11 exposure and Steps 11–21 stance change	$\beta=.73$	.012
GPT-4o Env-RP	Corresponding lagged rank association	$\rho=.410$	.0011
Gemini Eco-RP	Earlier exposure and later stance change	$\beta=1.04$	.003

Appendix

Table 19. Adjusted and lagged exposure associations. The text gives the corresponding model specifications.

Condition	$N$	Category changes	Mean trust $\pm$ SD
Eco-EP	30	7	$6.10\pm 1.03$
Env-EP	30	6	$6.83\pm 1.29$
Eco-RP	30	2	$6.57\pm 1.22$
Env-RP	30	12	$7.87\pm 0.82$

Appendix

Table 20. Categorical stance transitions and 10-point source ratings.

Figure 5. Categorical-study stance, source ratings and communication. Panel (a) shows final categories by preset group. Panels (b) to (e) show 10-point trust, and panels (f) to (i) show group-interaction matrices. All panels use the categorical study and its 10-point trust scale. Axis labels EA, EGS and NR refer to the preset groups. Stance distributions, source-rating boxplots and group communication matrices for the categorical study.

Figure 6. Reported trust by condition and preset group under the categorical protocol. Each row contains ten agents. Filled boxes show quartiles, lines mark medians, diamonds mark means and dots show recorded scores. Colours identify the three preset groups. Twelve horizontal trust boxplots from the original 120 agent records, on the original ten-point scale.

Figure 7. Affect and central-square occupancy across 21 steps. Panels (a) to (d) report mean summed VAD category scores by preset group. Panel (e) counts residents present in the central square. Markers denote saved values and connecting curves are spline interpolants. Four affect-summary trajectories and the combined central-square occupancy panel.

Agent	P1 strength	P1 rank	P2 strength	P2 rank	P3 strength	P3 rank
Ava Ramires	53	2	50	2.5	28	8.5
Caleb Morris	30	9.5	47	5	43	3
Eleanor Finch	54	1	52	1	41	4
Emily Novak	30	9.5	49	4	32	6
Jade Herrera	39	8	41	9	35	5
Jonas Müller	40	7	44	7.5	60	2

Appendix

Table 21. Interaction strengths and ranks for every primary-network agent.

Node	P1 strength	P1 rank	P2 strength	P2 rank	P3 strength	P3 rank
Researcher	37	9.5	47	7	71	2
Ava Ramires	53	3	63	1	28	11
Caleb Morris	37	9.5	48	6	45	5
Eleanor Finch	63	1	62	2	63	3.5
Emily Novak	30	11	53	3	37	7.5
Jade Herrera	39	8	45	8.5	36	9

Appendix

Table 22. Researcher-inclusive strengths and average-tie ranks.

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