Pith Number

pith:P2YUNYW3

pith:2026:P2YUNYW3AUQKQN2LNUZHSWYVS4

not attested not anchored not stored refs resolved

Adaptive Smooth Tchebycheff Attention for Multi-Objective Policy Optimization

Alejandro Murillo-Gonzalez, Lantao Liu, Mahmoud Ali

Dynamic modulation of Tchebycheff curvature via gradient conflict detection enables stable access to non-convex Pareto fronts in multi-objective robotic RL.

arxiv:2605.12771 v1 · 2026-05-12 · cs.RO · cs.AI · cs.LG · cs.SY · eess.SY · math.OC

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\usepackage{pith}
\pithnumber{P2YUNYW3AUQKQN2LNUZHSWYVS4}

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Extensive ablations confirm that our conflict-aware adaptation enables the robust discovery of Pareto-optimal policies in non-convex regions inaccessible to linear baselines and unstable for static non-linear methods.

C2weakest assumption

The conflict-driven controller can reliably detect destructive gradient interference in real time and modulate the scalarization curvature without introducing new sources of instability or bias in the policy gradient estimates.

C3one line summary

An adaptive smooth Tchebycheff controller for multi-objective RL lets agents reach non-convex Pareto regions in robotic tasks while avoiding the instability of static non-linear scalarizations.

References

87 extracted · 87 resolved · 2 Pith anchors

[1] Dynamic weights in multi- objective deep reinforcement learning 2019

[2] Spinning Up in Deep Reinforcement Learning, 2018 2018

[3] On the relationship of the tchebycheff norm and the efficient frontier of multiple- criteria objectives 1975

[4] Cambridge university press, 2004 2004

[5] Data- driven model predictive control for trajectory tracking with a robotic arm.IEEE Robotics and Automation Letters, 4(4):3758–3765, 2019 2019

Receipt and verification

First computed	2026-05-18T03:09:20.107648Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

7eb146e2db0520a8374b6d32795b15971b538772b27f615ad0536bd900dbc69c

Aliases

arxiv: 2605.12771 · arxiv_version: 2605.12771v1 · doi: 10.48550/arxiv.2605.12771 · pith_short_12: P2YUNYW3AUQK · pith_short_16: P2YUNYW3AUQKQN2L · pith_short_8: P2YUNYW3

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/P2YUNYW3AUQKQN2LNUZHSWYVS4 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 7eb146e2db0520a8374b6d32795b15971b538772b27f615ad0536bd900dbc69c

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "f8a1ed8dfe83f4857e1b184e5604de723d752304bd18d70f3e6edb9067b670c0",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.LG",
      "cs.SY",
      "eess.SY",
      "math.OC"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-05-12T21:32:57Z",
    "title_canon_sha256": "bae83624bea0cb24fd4a943bb419e079d493887784bf6c5e01e005696fb2be58"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.12771",
    "kind": "arxiv",
    "version": 1
  }
}