2 min readfrom Machine Learning

First A submission (AAMAS): how much theory is enough when your experiments went sideways? [D]

Hi everyone,

2nd-year PhD candidate here staring down my first A* submission deadline (AAMAS 2027). I could really use some perspective on theory expectations, especially since I think I’ve methodologically painted myself into a corner.

The setup

My project started with a clean hypothesis: if architecture X is more robust than Y to perturbation A, and B is a strictly harder version of A, then the X > Y ordering should hold under B as well. I isolated three variables I suspected were driving the effect, ran experiments, and… got results that only partially support the hypothesis, with clear boundary conditions.

Where I got stuck

Trying to explain the “why” mathematically sent me down a theory rabbit hole. I ended up with two bad options:

  1. Claims tied to specific training outputs rather than structural/architectural properties, or
  2. Weak, hand-wavy speculations that feel like post-hoc rationalizations.

I’m pretty sure I fell into HARKing.. I started building theory after seeing the results instead of deriving predictions beforehand.

Furthermore, my codebase is built on an undocumented public repo, and I recently found a bunch of hidden parameters set to wrong values for my setting. I’m currently re-running everything, which is why I’m being vague about specifics. My “insights” from the first round are probably garbage.

My actual questions

  • For those who’ve reviewed for or published at AAMAS (or similar A* venues): how much formal theory is actually expected for an empirical MARL paper? Is “here’s the phenomenon, here’s the controlled experiments, here’s a plausible but incomplete theoretical sketch” a death sentence?
  • If the theory ends up being training-dependent rather than structural, is that a sign I should pivot to a lower-tier venue, or can strong empirical characterization + limited theory still fly at A*?
  • How do you recover from HARKing mid-project when you’re under pressure to publish in year 3/4 of a 4-year contract?

Any advice on how to salvage the timeline or reframe the narrative would be hugely appreciated.

submitted by /u/ham_bam0
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Tagged with

#AAMAS
#MARL
#Multi-Agent Reinforcement Learning
#Theory
#Experiments
#HARKing
#Hypothesis
#A*
#Architecture
#Empirical Characterization
#Perturbation
#Post-hoc Rationalization
#Variables
#Training Outputs
#Structural Properties
#Venue
#Codebase
#Parameters
#Timeline
#Narrative